<?xml version="1.0" encoding="UTF-8"?>
 <rdf:RDF xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://web.resource.org/cc/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/">
  <channel rdf:about="http://pinboard.in">
    <title>Pinboard (WimLeers)</title>
    <link>https://pinboard.in/u:WimLeers/public/</link>
    <description>recent bookmarks from WimLeers</description>
    <items>
      <rdf:Seq>	<rdf:li rdf:resource="http://antirez.com/news/128"/>
	<rdf:li rdf:resource="https://brandur.org/canonical-log-lines"/>
	<rdf:li rdf:resource="https://twitter.com/LeaKissner/status/1083835229033254912"/>
	<rdf:li rdf:resource="https://www.calmtech.com/"/>
	<rdf:li rdf:resource="https://arstechnica.co.uk/features/2017/04/the-secret-lives-of-google-raters/?comments=1"/>
	<rdf:li rdf:resource="https://blog.acolyer.org/2017/03/10/chronix-long-term-storage-and-retrieval-technology-for-anomaly-detection-in-operational-data/"/>
	<rdf:li rdf:resource="https://theintercept.com/2017/03/02/palantir-provides-the-engine-for-donald-trumps-deportation-machine/"/>
	<rdf:li rdf:resource="http://highscalability.com/blog/2016/12/5/the-tech-that-turns-each-of-us-into-a-walled-garden.html"/>
	<rdf:li rdf:resource="https://m.signalvnoise.com/real-time-dashboards-considered-harmful-7ab026942ac#.x75vk2okc"/>
	<rdf:li rdf:resource="https://decorrespondent.nl/4391/Wanneer-data-dodelijk-kunnen-zijn/417235726842-ad181e75"/>
	<rdf:li rdf:resource="http://www.faz.net/aktuell/feuilleton/debatten/the-digital-debate/shoshana-zuboff-secrets-of-surveillance-capitalism-14103616-p2.html?printPagedArticle=true"/>
	<rdf:li rdf:resource="https://medium.com/@anabjain/how-will-we-live-d9baf00acac9#.wr0qn2an2"/>
	<rdf:li rdf:resource="http://blog.acolyer.org/2015/10/07/the-mystery-machine-end-to-end-performance-analysis-of-large-scale-internet-services/"/>
	<rdf:li rdf:resource="https://decorrespondent.nl/3478/Heel-Holland-Transparant-Zo-bepalen-bedrijven-en-overheden-of-je-een-risicoburger-bent/330481862436-0f840e0e"/>
	<rdf:li rdf:resource="http://waynechang.com/how-six-people-built-the-2-mobile-analytics-tool-in-just-a-few-months-full-article/"/>
	<rdf:li rdf:resource="http://www.cs.ucr.edu/~eamonn/meaningless.pdf"/>
	<rdf:li rdf:resource="https://decorrespondent.nl/2720/Baas-Belastingdienst-over-Big-Data-Mijn-missie-is-gedragsverandering/258456200640-93926f20"/>
	<rdf:li rdf:resource="http://www.r-bloggers.com/twitters-new-r-package-for-anomaly-detection/"/>
	<rdf:li rdf:resource="http://blogs.nature.com/news/2014/11/gates-foundation-announces-worlds-strongest-policy-on-open-access-research.html"/>
	<rdf:li rdf:resource="http://google.github.io/CausalImpact/"/>
	<rdf:li rdf:resource="http://practicalquant.blogspot.be/2012/10/mining-time-series-with-trillions-of.html?m=1"/>
	<rdf:li rdf:resource="http://conductrics.com/a-quick-tour-of-our-confidence-and-lift-report/"/>
	<rdf:li rdf:resource="http://www.wired.com/wiredscience/2014/01/how-to-hack-okcupid/all/"/>
	<rdf:li rdf:resource="http://awelonblue.wordpress.com/2013/01/24/exponential-decay-of-history-improved/"/>
	<rdf:li rdf:resource="http://www.thoughtgadgets.com/why-netflix-walked-away-from-personalization/"/>
	<rdf:li rdf:resource="http://conductrics.com/intelligent-agents-ab-testing-user-targeting-and-predictive-analytics/"/>
	<rdf:li rdf:resource="http://interana.com/#team"/>
	<rdf:li rdf:resource="http://m.standaard.be//cnt/dmf20131018_00797410"/>
	<rdf:li rdf:resource="http://stdout.be/2013/08/26/cargo-cult-analytics/"/>
	<rdf:li rdf:resource="http://jank.nicesho.es/"/>
	<rdf:li rdf:resource="https://github.com/occ/TraceKit"/>
	<rdf:li rdf:resource="https://github.com/cloudera/impala"/>
	<rdf:li rdf:resource="https://code.google.com/p/supersonic/"/>
	<rdf:li rdf:resource="https://github.com/gurgeh/selfspy"/>
	<rdf:li rdf:resource="http://highlyscalable.wordpress.com/2012/05/01/probabilistic-structures-web-analytics-data-mining/"/>
	<rdf:li rdf:resource="http://misoproject.com/dataset/"/>
	<rdf:li rdf:resource="http://dustin.github.com/2012/09/09/seriesly.html"/>
	<rdf:li rdf:resource="http://www.datadoghq.com/2012/08/easy-app-metrics-with-pup/"/>
	<rdf:li rdf:resource="http://www.aelag.com/147952673"/>
	<rdf:li rdf:resource="http://www.gooddata.com/"/>
	<rdf:li rdf:resource="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/8k7uBTYy0u8/data-jujitsu.html"/>
	<rdf:li rdf:resource="http://gigaom.com/cloud/why-the-days-are-numbered-for-hadoop-as-we-know-it/"/>
	<rdf:li rdf:resource="http://www.technologyreview.com/news/428402/automate-or-perish/"/>
	<rdf:li rdf:resource="http://anand.typepad.com/datawocky/2008/03/more-data-usual.html"/>
	<rdf:li rdf:resource="http://techcrunch.com/2012/06/27/citus-data-launches-new-scalable-analytics-database/"/>
	<rdf:li rdf:resource="http://www.techdirt.com/articles/20120619/04094319383/data-mining-exec-pays-burgers-cash-to-keep-his-insurance-company-knowing-his-bad-diet-habits.shtml"/>
	<rdf:li rdf:resource="http://blog.noblemail.ca/2012/05/analyst-measure-thyself.html"/>
	<rdf:li rdf:resource="http://radar.oreilly.com/2012/04/great-machine-learning-products.html"/>
	<rdf:li rdf:resource="http://radar.oreilly.com/2012/02/data-public-good.html"/>
	<rdf:li rdf:resource="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/1pJ1fSZVieI/operations-machine-learning-data.html"/>
	<rdf:li rdf:resource="http://www.principalcomponentswanted.com/"/>
	<rdf:li rdf:resource="http://www.informationweek.com/news/government/enterprise-apps/232800018"/>
	<rdf:li rdf:resource="http://radar.oreilly.com/2012/03/data-science-deep-data-information-paradox.html"/>
	<rdf:li rdf:resource="http://www.ritholtz.com/blog/2012/03/linkedin-industry-trends/"/>
	<rdf:li rdf:resource="http://code.google.com/p/bayon/"/>
	<rdf:li rdf:resource="http://cameronneylon.net/blog/they-just-dont-get-it/"/>
	<rdf:li rdf:resource="http://research.yahoo.com/files/Web-Scale%20User%20Modeling%20for%20Targeting.pdf"/>
	<rdf:li rdf:resource="http://netto.tijd.be/geld_en_gezin/belastingen/Wie_pikt_de_fiscus_eruit_voor_controle.9166628-1624.art"/>
	<rdf:li rdf:resource="http://m.techcrunch.com/2012/02/19/unhyped-internet-and-mobile/"/>
	<rdf:li rdf:resource="http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?_r=3&amp;pagewanted=all"/>
	<rdf:li rdf:resource="http://blog.kissmetrics.com/data-mining/"/>
	<rdf:li rdf:resource="http://datasift.com/"/>
	<rdf:li rdf:resource="http://en.wikipedia.org/wiki/Production_system"/>
	<rdf:li rdf:resource="http://www.igvita.com/2010/01/06/flow-analysis-time-based-bloom-filters/"/>
	<rdf:li rdf:resource="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/y6duPHoqR30/hadoop-doug-cutting-apache-data-processing.html"/>
	<rdf:li rdf:resource="http://stackoverflow.com/questions/7237271/large-scale-data-processing-hbase-vs-cassandra/7238818#7238818"/>
	<rdf:li rdf:resource="http://highscalability.com/blog/2011/3/22/facebooks-new-realtime-analytics-system-hbase-to-process-20.html"/>
	<rdf:li rdf:resource="http://infolab.stanford.edu/~echang/recsys08-69.pdf"/>
	<rdf:li rdf:resource="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/Nzb4Suglj3I/narrative-science-kristian-hammond-data-content-generation.html"/>
	<rdf:li rdf:resource="http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-intelligence/complex-event-processing.aspx"/>
      </rdf:Seq>
    </items>
  </channel><item rdf:about="http://antirez.com/news/128">
    <title>Redis streams as a pure data structure - &lt;antirez&gt;</title>
    <dc:date>2019-03-23T10:26:27+00:00</dc:date>
    <link>http://antirez.com/news/128</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>redis datastructures datamining streaming</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:8579fe44b461/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:redis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datastructures"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:streaming"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://brandur.org/canonical-log-lines">
    <title>Using Canonical Log Lines for Online Visibility — Brandur Leach</title>
    <dc:date>2019-01-20T00:26:51+00:00</dc:date>
    <link>https://brandur.org/canonical-log-lines</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>logging monitoring datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:96ad96045a38/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:logging"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:monitoring"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://twitter.com/LeaKissner/status/1083835229033254912">
    <title>Lea Kissner on Twitter</title>
    <dc:date>2019-01-12T11:03:06+00:00</dc:date>
    <link>https://twitter.com/LeaKissner/status/1083835229033254912</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>data datamining privacy</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:a2cedb4aec46/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.calmtech.com/">
    <title>Calm Technology</title>
    <dc:date>2017-05-02T13:01:54+00:00</dc:date>
    <link>https://www.calmtech.com/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>software privacy datamining reference</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:12ea85d44c35/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:software"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arstechnica.co.uk/features/2017/04/the-secret-lives-of-google-raters/?comments=1">
    <title>The secret lives of Google raters | Ars Technica UK</title>
    <dc:date>2017-04-29T19:31:11+00:00</dc:date>
    <link>https://arstechnica.co.uk/features/2017/04/the-secret-lives-of-google-raters/?comments=1</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>google evil datamining machinelearning</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:f8525c51216c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:evil"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:machinelearning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://blog.acolyer.org/2017/03/10/chronix-long-term-storage-and-retrieval-technology-for-anomaly-detection-in-operational-data/">
    <title>Chronix: Long term storage and retrieval technology for anomaly detection in operational data | the morning paper</title>
    <dc:date>2017-03-12T18:03:07+00:00</dc:date>
    <link>https://blog.acolyer.org/2017/03/10/chronix-long-term-storage-and-retrieval-technology-for-anomaly-detection-in-operational-data/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:43b3c7effcac/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://theintercept.com/2017/03/02/palantir-provides-the-engine-for-donald-trumps-deportation-machine/">
    <title>Palantir Provides the Engine for Donald Trump’s Deportation Machine</title>
    <dc:date>2017-03-04T15:11:09+00:00</dc:date>
    <link>https://theintercept.com/2017/03/02/palantir-provides-the-engine-for-donald-trumps-deportation-machine/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>usa donaldtrump datamining evil epicfail</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:648cf97d3568/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:usa"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:donaldtrump"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:evil"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:epicfail"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://highscalability.com/blog/2016/12/5/the-tech-that-turns-each-of-us-into-a-walled-garden.html">
    <title>The Tech that Turns Each of Us Into a Walled Garden - High Scalability -</title>
    <dc:date>2016-12-06T18:27:43+00:00</dc:date>
    <link>http://highscalability.com/blog/2016/12/5/the-tech-that-turns-each-of-us-into-a-walled-garden.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining predictiveanalytics socialmedia advertising psychology facebook politics evil</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:3383ba0945bd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:predictiveanalytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:socialmedia"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:advertising"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:facebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:politics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:evil"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://m.signalvnoise.com/real-time-dashboards-considered-harmful-7ab026942ac#.x75vk2okc">
    <title>Real-time dashboards considered harmful — Signal v. Noise</title>
    <dc:date>2016-06-26T16:29:42+00:00</dc:date>
    <link>https://m.signalvnoise.com/real-time-dashboards-considered-harmful-7ab026942ac#.x75vk2okc</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining statistics startup realtime</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:d36b9811a434/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:startup"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:realtime"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://decorrespondent.nl/4391/Wanneer-data-dodelijk-kunnen-zijn/417235726842-ad181e75">
    <title>Wanneer data dodelijk kunnen zijn</title>
    <dc:date>2016-05-23T09:28:47+00:00</dc:date>
    <link>https://decorrespondent.nl/4391/Wanneer-data-dodelijk-kunnen-zijn/417235726842-ad181e75</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>data datamining privacy</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:cd4389a1b0ee/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.faz.net/aktuell/feuilleton/debatten/the-digital-debate/shoshana-zuboff-secrets-of-surveillance-capitalism-14103616-p2.html?printPagedArticle=true">
    <title>Shoshana Zuboff: Secrets of Surveillance Capitalism</title>
    <dc:date>2016-03-21T08:48:22+00:00</dc:date>
    <link>http://www.faz.net/aktuell/feuilleton/debatten/the-digital-debate/shoshana-zuboff-secrets-of-surveillance-capitalism-14103616-p2.html?printPagedArticle=true</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>advertising capitalism surveillance business reference privacy google datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:e86c57789655/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:advertising"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:capitalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:surveillance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:business"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://medium.com/@anabjain/how-will-we-live-d9baf00acac9#.wr0qn2an2">
    <title>How Will We Live — Medium</title>
    <dc:date>2015-10-26T07:21:54+00:00</dc:date>
    <link>https://medium.com/@anabjain/how-will-we-live-d9baf00acac9#.wr0qn2an2</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>future society datamining privacy</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:9d0750260549/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:future"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:society"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.acolyer.org/2015/10/07/the-mystery-machine-end-to-end-performance-analysis-of-large-scale-internet-services/">
    <title>The Mystery Machine: End-to-end performance analysis of large-scale internet services | the morning paper</title>
    <dc:date>2015-10-21T17:18:46+00:00</dc:date>
    <link>http://blog.acolyer.org/2015/10/07/the-mystery-machine-end-to-end-performance-analysis-of-large-scale-internet-services/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>facebook algorithms datamining profiling performance</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:5a1804d93e2f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:facebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:profiling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:performance"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://decorrespondent.nl/3478/Heel-Holland-Transparant-Zo-bepalen-bedrijven-en-overheden-of-je-een-risicoburger-bent/330481862436-0f840e0e">
    <title>De Correspondent</title>
    <dc:date>2015-10-13T06:29:17+00:00</dc:date>
    <link>https://decorrespondent.nl/3478/Heel-Holland-Transparant-Zo-bepalen-bedrijven-en-overheden-of-je-een-risicoburger-bent/330481862436-0f840e0e</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining bigdata privacy</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:bcb094b6e491/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://waynechang.com/how-six-people-built-the-2-mobile-analytics-tool-in-just-a-few-months-full-article/">
    <title>How six people built the #2 mobile analytics tool in just a few months</title>
    <dc:date>2015-06-06T22:34:45+00:00</dc:date>
    <link>http://waynechang.com/how-six-people-built-the-2-mobile-analytics-tool-in-just-a-few-months-full-article/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>startup datamining analytics twitter</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:a79cf661ab2f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:startup"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:analytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.cs.ucr.edu/~eamonn/meaningless.pdf">
    <title>[untitled]</title>
    <dc:date>2015-04-26T20:00:55+00:00</dc:date>
    <link>http://www.cs.ucr.edu/~eamonn/meaningless.pdf</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:8b1e5764a59a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://decorrespondent.nl/2720/Baas-Belastingdienst-over-Big-Data-Mijn-missie-is-gedragsverandering/258456200640-93926f20">
    <title>Baas Belastingdienst over Big Data: 'Mijn missie is gedragsverandering'</title>
    <dc:date>2015-04-21T08:02:26+00:00</dc:date>
    <link>https://decorrespondent.nl/2720/Baas-Belastingdienst-over-Big-Data-Mijn-missie-is-gedragsverandering/258456200640-93926f20</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>taxes government netherlands datamining privacy history 2015</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:162d6d01270d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:taxes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:government"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:netherlands"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:2015"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.r-bloggers.com/twitters-new-r-package-for-anomaly-detection/">
    <title>Twitter’s new R package for anomaly detection | R-bloggers</title>
    <dc:date>2015-01-08T13:49:40+00:00</dc:date>
    <link>http://www.r-bloggers.com/twitters-new-r-package-for-anomaly-detection/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>statistics datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:37aa8cdbbb5d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blogs.nature.com/news/2014/11/gates-foundation-announces-worlds-strongest-policy-on-open-access-research.html">
    <title>Gates Foundation announces world’s strongest policy on open access research : Nature News Blog</title>
    <dc:date>2014-11-28T20:10:30+00:00</dc:date>
    <link>http://blogs.nature.com/news/2014/11/gates-foundation-announces-worlds-strongest-policy-on-open-access-research.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>academics research BillGates innovation datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:172065fff489/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:academics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:research"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:BillGates"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:innovation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://google.github.io/CausalImpact/">
    <title>CausalImpact</title>
    <dc:date>2014-09-15T20:43:19+00:00</dc:date>
    <link>http://google.github.io/CausalImpact/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>wpo performance datamining algorithms statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:ea463aa25a6e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:wpo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://practicalquant.blogspot.be/2012/10/mining-time-series-with-trillions-of.html?m=1">
    <title>Mining Time-series with Trillions of Points: Dynamic Time Warping at scale</title>
    <dc:date>2014-07-26T19:12:32+00:00</dc:date>
    <link>http://practicalquant.blogspot.be/2012/10/mining-time-series-with-trillions-of.html?m=1</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining algorithms medicine future history 2014 reference</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:d926f7c1a037/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:medicine"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:future"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:2014"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://conductrics.com/a-quick-tour-of-our-confidence-and-lift-report/">
    <title>Conductrics' Confidence and Lift Report - The Basics | Conductrics</title>
    <dc:date>2014-07-26T19:04:16+00:00</dc:date>
    <link>http://conductrics.com/a-quick-tour-of-our-confidence-and-lift-report/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>statistics datamining acquia</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:a78ea9c0bb5c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:acquia"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.wired.com/wiredscience/2014/01/how-to-hack-okcupid/all/">
    <title>How a Math Genius Hacked OkCupid to Find True Love</title>
    <dc:date>2014-01-22T13:04:16+00:00</dc:date>
    <link>http://www.wired.com/wiredscience/2014/01/how-to-hack-okcupid/all/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining dating statistics aw</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:47c5bc9be5f2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:dating"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:aw"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://awelonblue.wordpress.com/2013/01/24/exponential-decay-of-history-improved/">
    <title>Exponential Decay of History, Improved | Awelon Blue</title>
    <dc:date>2014-01-13T08:39:30+00:00</dc:date>
    <link>http://awelonblue.wordpress.com/2013/01/24/exponential-decay-of-history-improved/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:37d37f616780/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.thoughtgadgets.com/why-netflix-walked-away-from-personalization/">
    <title>Why Netflix walked away from personalization | ThoughtGadgets</title>
    <dc:date>2014-01-06T10:53:47+00:00</dc:date>
    <link>http://www.thoughtgadgets.com/why-netflix-walked-away-from-personalization/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>personalization datamining reference psychology</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:1de856fc9438/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:personalization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:psychology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://conductrics.com/intelligent-agents-ab-testing-user-targeting-and-predictive-analytics/">
    <title>Intelligent Agents: AB Testing, User Targeting, and Predictive Analytics</title>
    <dc:date>2013-11-10T21:18:53+00:00</dc:date>
    <link>http://conductrics.com/intelligent-agents-ab-testing-user-targeting-and-predictive-analytics/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:bda4620eaa20/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://interana.com/#team">
    <title>Interana</title>
    <dc:date>2013-10-24T15:55:59+00:00</dc:date>
    <link>http://interana.com/#team</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>facebook analytics datamining liorabraham</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:4216a49ce96d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:facebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:analytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:liorabraham"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://m.standaard.be//cnt/dmf20131018_00797410">
    <title>Computerprogramma wijst fraudeurs aan - De Standaard Mobile</title>
    <dc:date>2013-10-19T09:03:05+00:00</dc:date>
    <link>http://m.standaard.be//cnt/dmf20131018_00797410</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>belgium datamining tax fraud history 2013</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:cb591a393913/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:belgium"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:tax"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:fraud"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:2013"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://stdout.be/2013/08/26/cargo-cult-analytics/">
    <title>Cargo cult analytics</title>
    <dc:date>2013-09-15T16:50:06+00:00</dc:date>
    <link>http://stdout.be/2013/08/26/cargo-cult-analytics/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining analytics theguardian journalism</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:7ef6504bb82c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:analytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:theguardian"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:journalism"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://jank.nicesho.es/">
    <title>welcoem</title>
    <dc:date>2013-03-18T17:46:23+00:00</dc:date>
    <link>http://jank.nicesho.es/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>okayzed datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:2038d2a15d42/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:okayzed"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/occ/TraceKit">
    <title>TraceKit</title>
    <dc:date>2012-12-13T14:03:06+00:00</dc:date>
    <link>https://github.com/occ/TraceKit</link>
    <dc:creator>WimLeers</dc:creator><description><![CDATA[@nod_ Did you see this? ]]></description>
<dc:subject>javascript datamining</dc:subject>
<dc:source>https://twitter.com/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:af21a82216eb/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:javascript"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/cloudera/impala">
    <title>Impala (Four short links: 25 October 2012)</title>
    <dc:date>2012-10-25T20:29:18+00:00</dc:date>
    <link>https://github.com/cloudera/impala</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining bigdata performance algorithms cloudera</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:ecda067953b0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:cloudera"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://code.google.com/p/supersonic/">
    <title>supersonic - Supersonic Query Engine - a column oriented database query engine library. - Google Project Hosting</title>
    <dc:date>2012-10-25T20:28:01+00:00</dc:date>
    <link>https://code.google.com/p/supersonic/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining bigdata c++ performance algorithms</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:3de670a8e5ec/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:c++"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/gurgeh/selfspy">
    <title>selfspy</title>
    <dc:date>2012-10-02T06:07:10+00:00</dc:date>
    <link>https://github.com/gurgeh/selfspy</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining privacy quantifiedself</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:c3fc3a2c8820/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:quantifiedself"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://highlyscalable.wordpress.com/2012/05/01/probabilistic-structures-web-analytics-data-mining/">
    <title>Probabilistic Data Structures for Web Analytics and Data Mining</title>
    <dc:date>2012-09-15T22:04:31+00:00</dc:date>
    <link>http://highlyscalable.wordpress.com/2012/05/01/probabilistic-structures-web-analytics-data-mining/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining datastructures algorithms statistics referen e</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:02cf49a2d7bf/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datastructures"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:referen"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:e"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://misoproject.com/dataset/">
    <title>Dataset</title>
    <dc:date>2012-09-14T20:46:13+00:00</dc:date>
    <link>http://misoproject.com/dataset/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>javascript datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:88372a7eb865/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:javascript"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://dustin.github.com/2012/09/09/seriesly.html">
    <title>Seriesly - Document Oriented Time Series DB</title>
    <dc:date>2012-09-14T08:10:39+00:00</dc:date>
    <link>http://dustin.github.com/2012/09/09/seriesly.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>charts go time db datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:400990edb9b3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:charts"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:go"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:time"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:db"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.datadoghq.com/2012/08/easy-app-metrics-with-pup/">
    <title>Datadog - Easy app metrics with Pup</title>
    <dc:date>2012-08-06T18:00:35+00:00</dc:date>
    <link>http://www.datadoghq.com/2012/08/easy-app-metrics-with-pup/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>statistics analytics statsd charts wpo datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:c00e6f0fc199/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:analytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:statsd"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:charts"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:wpo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.aelag.com/147952673">
    <title>Machine learning for the impatient: algorithms tuning algorithms</title>
    <dc:date>2012-08-05T17:19:20+00:00</dc:date>
    <link>http://www.aelag.com/147952673</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:444e7ab26b27/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.gooddata.com/">
    <title>SaaS Business Intelligence Software, Dashboards, Analytics | GoodData</title>
    <dc:date>2012-07-22T13:02:07+00:00</dc:date>
    <link>http://www.gooddata.com/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>bigdata datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:426eae378a65/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/8k7uBTYy0u8/data-jujitsu.html">
    <title>Data Jujitsu: The art of turning data into product</title>
    <dc:date>2012-07-19T23:15:25+00:00</dc:date>
    <link>http://feedproxy.google.com/~r/oreilly/radar/atom/~3/8k7uBTYy0u8/data-jujitsu.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>data datamining datascience</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:27c65d201b8d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datascience"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://gigaom.com/cloud/why-the-days-are-numbered-for-hadoop-as-we-know-it/">
    <title>Why the days are numbered for Hadoop as we know it — Cloud Computing News</title>
    <dc:date>2012-07-08T06:42:07+00:00</dc:date>
    <link>http://gigaom.com/cloud/why-the-days-are-numbered-for-hadoop-as-we-know-it/</link>
    <dc:creator>WimLeers</dc:creator><description><![CDATA[RT @Dries: Why the days are numbered for Hadoop as we know it ]]></description>
<dc:subject>hadoop mapreduce bigdata datamining</dc:subject>
<dc:source>https://twitter.com/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:9d4e4a95766c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:hadoop"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:mapreduce"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.technologyreview.com/news/428402/automate-or-perish/">
    <title>Automate or Perish</title>
    <dc:date>2012-07-06T11:35:03+00:00</dc:date>
    <link>http://www.technologyreview.com/news/428402/automate-or-perish/</link>
    <dc:creator>WimLeers</dc:creator><description><![CDATA[Must-read: "Automate or Perish" — ]]></description>
<dc:subject>career work programming computer automation datamining future history mustread fb</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:7fa4d367fd31/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:career"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:work"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:programming"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:computer"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:automation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:future"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:mustread"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:fb"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://anand.typepad.com/datawocky/2008/03/more-data-usual.html">
    <title>Datawocky</title>
    <dc:date>2012-07-02T07:28:36+00:00</dc:date>
    <link>http://anand.typepad.com/datawocky/2008/03/more-data-usual.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:ec2614647401/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://techcrunch.com/2012/06/27/citus-data-launches-new-scalable-analytics-database/">
    <title>Y Combinator Alum Citus Data Wants To Make Scalable Data Analytics Accessible To Anyone</title>
    <dc:date>2012-06-30T07:25:31+00:00</dc:date>
    <link>http://techcrunch.com/2012/06/27/citus-data-launches-new-scalable-analytics-database/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>database datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:390ba41e745a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:database"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.techdirt.com/articles/20120619/04094319383/data-mining-exec-pays-burgers-cash-to-keep-his-insurance-company-knowing-his-bad-diet-habits.shtml">
    <title>Data Mining Exec Pays For Burgers In Cash To Keep His Insurance Company From Knowing His Bad Diet Habits</title>
    <dc:date>2012-06-23T17:13:01+00:00</dc:date>
    <link>http://www.techdirt.com/articles/20120619/04094319383/data-mining-exec-pays-burgers-cash-to-keep-his-insurance-company-knowing-his-bad-diet-habits.shtml</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>insurance bigdata datamining health privacy</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:1946a8999ed6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:insurance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:health"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.noblemail.ca/2012/05/analyst-measure-thyself.html">
    <title>Analyst, measure thyself</title>
    <dc:date>2012-05-06T10:43:08+00:00</dc:date>
    <link>http://blog.noblemail.ca/2012/05/analyst-measure-thyself.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:275c9b534bc0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://radar.oreilly.com/2012/04/great-machine-learning-products.html">
    <title>What it takes to build great machine learning products - O'Reilly Radar</title>
    <dc:date>2012-04-17T07:36:12+00:00</dc:date>
    <link>http://radar.oreilly.com/2012/04/great-machine-learning-products.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>machinelearning datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:b9be03e6d352/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://radar.oreilly.com/2012/02/data-public-good.html">
    <title>Data for the public good</title>
    <dc:date>2012-04-09T23:52:37+00:00</dc:date>
    <link>http://radar.oreilly.com/2012/02/data-public-good.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>opendata datamining government</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:37e8a1c753b0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:opendata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:government"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/1pJ1fSZVieI/operations-machine-learning-data.html">
    <title>Operations, machine learning and premature babies</title>
    <dc:date>2012-04-09T23:49:22+00:00</dc:date>
    <link>http://feedproxy.google.com/~r/oreilly/radar/atom/~3/1pJ1fSZVieI/operations-machine-learning-data.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>wpo datamining medicine aw</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:3dddf7a29ffa/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:wpo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:medicine"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:aw"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.principalcomponentswanted.com/">
    <title>Principal Components Wanted</title>
    <dc:date>2012-04-08T22:29:54+00:00</dc:date>
    <link>http://www.principalcomponentswanted.com/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>machinelearning startup datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:acbce327ca00/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:startup"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.informationweek.com/news/government/enterprise-apps/232800018">
    <title>FBI's New Sentinel System</title>
    <dc:date>2012-04-08T22:25:07+00:00</dc:date>
    <link>http://www.informationweek.com/news/government/enterprise-apps/232800018</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>usa fbi datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:ebf5a335e80c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:usa"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:fbi"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://radar.oreilly.com/2012/03/data-science-deep-data-information-paradox.html">
    <title>Automated science, deep data and the paradox of information</title>
    <dc:date>2012-03-31T12:33:32+00:00</dc:date>
    <link>http://radar.oreilly.com/2012/03/data-science-deep-data-information-paradox.html</link>
    <dc:creator>WimLeers</dc:creator><description><![CDATA[Must-read: "Automated science, deep data and the paradox... ]]></description>
<dc:subject>science datamining datascience analytics reference aw mustread</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:dee81cb556b2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datascience"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:analytics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:aw"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:mustread"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.ritholtz.com/blog/2012/03/linkedin-industry-trends/">
    <title>Macro Perspective on the Capital Markets, Economy, Technology, and Digital Media</title>
    <dc:date>2012-03-15T16:13:58+00:00</dc:date>
    <link>http://www.ritholtz.com/blog/2012/03/linkedin-industry-trends/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>linkedin datamining economics</dc:subject>
<dc:source>https://twitter.com/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:b9fbdfd9a694/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:linkedin"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:economics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://code.google.com/p/bayon/">
    <title>a simple and fast clustering tool</title>
    <dc:date>2012-03-14T19:57:02+00:00</dc:date>
    <link>http://code.google.com/p/bayon/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:91258e350b33/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://cameronneylon.net/blog/they-just-dont-get-it/">
    <title>They. Just. Don’t. Get. It… « Science in the Open</title>
    <dc:date>2012-03-12T11:49:05+00:00</dc:date>
    <link>http://cameronneylon.net/blog/they-just-dont-get-it/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining future history</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:9bbfe63b1ed7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:future"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:history"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://research.yahoo.com/files/Web-Scale%20User%20Modeling%20for%20Targeting.pdf">
    <title>Web-Scale User Modeling for Targeting (Four short links: 12 March 2012)</title>
    <dc:date>2012-03-12T10:42:16+00:00</dc:date>
    <link>http://research.yahoo.com/files/Web-Scale%20User%20Modeling%20for%20Targeting.pdf</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining realtime</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:f5e1c89b774e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:realtime"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://netto.tijd.be/geld_en_gezin/belastingen/Wie_pikt_de_fiscus_eruit_voor_controle.9166628-1624.art">
    <title>Wie pikt de fiscus eruit voor controle?</title>
    <dc:date>2012-03-07T11:37:12+00:00</dc:date>
    <link>http://netto.tijd.be/geld_en_gezin/belastingen/Wie_pikt_de_fiscus_eruit_voor_controle.9166628-1624.art</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>belgium datamining taxes government</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:dbdb828d23b3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:belgium"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:taxes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:government"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://m.techcrunch.com/2012/02/19/unhyped-internet-and-mobile/">
    <title>The “Unhyped” New Areas in Internet and Mobile</title>
    <dc:date>2012-02-21T09:46:52+00:00</dc:date>
    <link>http://m.techcrunch.com/2012/02/19/unhyped-internet-and-mobile/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining startup</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:aa8ed452cca4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:startup"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?_r=3&amp;pagewanted=all">
    <title>How Companies Learn Your Secrets - NYTimes.com</title>
    <dc:date>2012-02-17T11:43:11+00:00</dc:date>
    <link>http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?_r=3&amp;pagewanted=all</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining privacy shopping aw reference</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:25e19b9a229a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:shopping"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:aw"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:reference"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.kissmetrics.com/data-mining/">
    <title>10 Ways Data Mining Can Help You Get a Competitive Edge</title>
    <dc:date>2012-02-15T12:26:43+00:00</dc:date>
    <link>http://blog.kissmetrics.com/data-mining/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:2c3b1ec5b806/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://datasift.com/">
    <title>DataSift | Data On Demand</title>
    <dc:date>2012-02-14T16:11:44+00:00</dc:date>
    <link>http://datasift.com/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining socialmedia</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:db088c3dedde/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:socialmedia"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://en.wikipedia.org/wiki/Production_system">
    <title>Production system - Wikipedia, the free encyclopedia</title>
    <dc:date>2012-02-14T14:13:54+00:00</dc:date>
    <link>http://en.wikipedia.org/wiki/Production_system</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:0e7991e4921d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.igvita.com/2010/01/06/flow-analysis-time-based-bloom-filters/">
    <title>Flow Analysis &amp; Time-based Bloom Filters</title>
    <dc:date>2012-02-08T12:49:16+00:00</dc:date>
    <link>http://www.igvita.com/2010/01/06/flow-analysis-time-based-bloom-filters/</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>algorithms bloom redis datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:f8cd312b09fc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bloom"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:redis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/y6duPHoqR30/hadoop-doug-cutting-apache-data-processing.html">
    <title>Why Hadoop caught on</title>
    <dc:date>2012-02-08T08:34:55+00:00</dc:date>
    <link>http://feedproxy.google.com/~r/oreilly/radar/atom/~3/y6duPHoqR30/hadoop-doug-cutting-apache-data-processing.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>hadoop bigdata datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:cbe5e1e0de08/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:hadoop"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:bigdata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://stackoverflow.com/questions/7237271/large-scale-data-processing-hbase-vs-cassandra/7238818#7238818">
    <title>nosql - Large scale data processing Hbase vs Cassandra - Stack Overflow</title>
    <dc:date>2012-02-07T14:39:48+00:00</dc:date>
    <link>http://stackoverflow.com/questions/7237271/large-scale-data-processing-hbase-vs-cassandra/7238818#7238818</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining scalability cassandra nosql</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:efb43265cdd7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:scalability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:cassandra"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:nosql"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://highscalability.com/blog/2011/3/22/facebooks-new-realtime-analytics-system-hbase-to-process-20.html">
    <title>High Scalability - High Scalability - Facebook's New Realtime Analytics System: HBase to Process 20 Billion Events Per Day</title>
    <dc:date>2012-02-07T14:35:31+00:00</dc:date>
    <link>http://highscalability.com/blog/2011/3/22/facebooks-new-realtime-analytics-system-hbase-to-process-20.html</link>
    <dc:creator>WimLeers</dc:creator><description><![CDATA[Ptail]]></description>
<dc:subject>facebook scalability datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:f6fc9de00493/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:facebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:scalability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://infolab.stanford.edu/~echang/recsys08-69.pdf">
    <title>[untitled]</title>
    <dc:date>2012-02-07T13:39:48+00:00</dc:date>
    <link>http://infolab.stanford.edu/~echang/recsys08-69.pdf</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:WimLeers/b:122dee84b296/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://feedproxy.google.com/~r/oreilly/radar/atom/~3/Nzb4Suglj3I/narrative-science-kristian-hammond-data-content-generation.html">
    <title>Transforming data into narrative content</title>
    <dc:date>2012-01-29T09:38:42+00:00</dc:date>
    <link>http://feedproxy.google.com/~r/oreilly/radar/atom/~3/Nzb4Suglj3I/narrative-science-kristian-hammond-data-content-generation.html</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:e7af14aab73b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-intelligence/complex-event-processing.aspx">
    <title>StreamInsight (Microsoft's plan for Hadoop and big data)</title>
    <dc:date>2012-01-29T09:36:49+00:00</dc:date>
    <link>http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-intelligence/complex-event-processing.aspx</link>
    <dc:creator>WimLeers</dc:creator><dc:subject>datamining</dc:subject>
<dc:identifier>https://pinboard.in/u:WimLeers/b:7a0ce60dd5a4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:WimLeers/t:datamining"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>