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<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/tag/textmining"><title>BibSonomy bookmarks for /tag/textmining</title><link>https://www.bibsonomy.org/tag/textmining</link><description>BibSonomy RSS Feed for /tag/textmining</description><items><rdf:Seq><rdf:li rdf:resource="https://timswww.wordpress.com/2018/07/01/evaluation-and-automatic-analysis-of-mooc-forum-comments/"/><rdf:li rdf:resource="https://voyant-tools.org/"/><rdf:li rdf:resource="https://www.tidytextmining.com/"/><rdf:li rdf:resource="http://sjgknight.com/finding-knowledge/2017/04/tools-for-analysing-learning-texts/"/><rdf:li rdf:resource="https://nlp.stanford.edu/IR-book/html/htmledition/latent-semantic-indexing-1.html"/><rdf:li rdf:resource="http://tidytextmining.com/index.html"/><rdf:li rdf:resource="http://www.textpresso.org/"/><rdf:li rdf:resource="https://georeferenced.wordpress.com/2013/01/15/rwordcloud/"/><rdf:li rdf:resource="http://contentmine.org/"/><rdf:li rdf:resource="http://gisele.underarmour.com/"/><rdf:li rdf:resource="https://jaibeermalik.wordpress.com/2013/03/26/elasticsearch-text-analysis-for-content-enrichment/"/><rdf:li rdf:resource="http://blog.florian-hopf.de/2013/09/simple-event-analytics-with.html"/><rdf:li rdf:resource="https://github.com/spinscale/elasticsearch-opennlp-plugin"/><rdf:li rdf:resource="https://github.com/pandastrike/bayzee"/><rdf:li rdf:resource="https://github.com/polyfractal/ElasticBayes"/><rdf:li rdf:resource="https://uima.apache.org/"/><rdf:li rdf:resource="http://www.newsreader-project.eu/"/><rdf:li rdf:resource="https://uima.apache.org/"/><rdf:li rdf:resource="http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track"/><rdf:li rdf:resource="http://www.r-bloggers.com/text-mining-in-r-automatic-categorization-of-wikipedia-articles/"/></rdf:Seq></items></channel><item rdf:about="https://timswww.wordpress.com/2018/07/01/evaluation-and-automatic-analysis-of-mooc-forum-comments/"><title>Evaluation and automatic analysis of MOOC forum comments – Tim&#039;s World of Web</title><description>My doctoral thesis is available to download via the University of Southampton&#039;s ePrints site.</description><link>https://timswww.wordpress.com/2018/07/01/evaluation-and-automatic-analysis-of-mooc-forum-comments/</link><dc:creator>ereidt</dc:creator><dc:date>2019-06-23T10:47:49+02:00</dc:date><dc:subject>MOOC actionablefeedback criticalthinking dissertation evaluation learninganalytics papers textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;My doctoral thesis is available to download via the University of Southampton&amp;#039;s ePrints site.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/MOOC"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/actionablefeedback"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/criticalthinking"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dissertation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/evaluation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learninganalytics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/papers"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://voyant-tools.org/"><title>Voyant Tools</title><description>Voyant Tools is a web-based text reading and analysis environment. It is a scholarly project that is designed to facilitate reading and interpretive practices for digital humanities students and scholars as well as for the general public.

What you can do with Voyant:

    Use it to learn how computers-assisted analysis works. Check out our examples that show you how to do real academic tasks with Voyant.
    Use it to study texts that you find on the web or texts that you have carefully edited and have on your computer.
    Use it to add functionality to your online collections, journals, blogs or web sites so others can see through your texts with analytical tools.
    Use it to add interactive evidence to your essays that you publish online. Add interactive panels right into your research essays (if they can be published online) so your readers can recapitulate your results.
    Use it to develop your own tools using our functionality and code.
</description><link>https://voyant-tools.org/</link><dc:creator>djimenezsanchez</dc:creator><dc:date>2018-11-07T09:44:33+01:00</dc:date><dc:subject>analisis_discurso cualitativa digital_humanities herramientas textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Voyant Tools is a web-based text reading and analysis environment. It is a scholarly project that is designed to facilitate reading and interpretive practices for digital humanities students and scholars as well as for the general public.

What you can do with Voyant:

    Use it to learn how computers-assisted analysis works. Check out our examples that show you how to do real academic tasks with Voyant.
    Use it to study texts that you find on the web or texts that you have carefully edited and have on your computer.
    Use it to add functionality to your online collections, journals, blogs or web sites so others can see through your texts with analytical tools.
    Use it to add interactive evidence to your essays that you publish online. Add interactive panels right into your research essays (if they can be published online) so your readers can recapitulate your results.
    Use it to develop your own tools using our functionality and code.
&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analisis_discurso"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cualitativa"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/digital_humanities"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/herramientas"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.tidytextmining.com/"><title>Text Mining with R</title><description>A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools</description><link>https://www.tidytextmining.com/</link><dc:creator>avs</dc:creator><dc:date>2018-03-13T10:47:45+01:00</dc:date><dc:subject>Digital_Humanities R Textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Digital_Humanities"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/R"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://sjgknight.com/finding-knowledge/2017/04/tools-for-analysing-learning-texts/"><title>Tools for analysing learning texts | Finding Knowledge</title><description>a bit of a random selection of some tools</description><link>http://sjgknight.com/finding-knowledge/2017/04/tools-for-analysing-learning-texts/</link><dc:creator>ereidt</dc:creator><dc:date>2017-04-30T13:00:47+02:00</dc:date><dc:subject>learninganalytics socialmedia statistics textmining visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;a bit of a random selection of some tools&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learninganalytics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/socialmedia"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="https://nlp.stanford.edu/IR-book/html/htmledition/latent-semantic-indexing-1.html"><title>Latent semantic indexing</title><description>Latent semantic indexing</description><link>https://nlp.stanford.edu/IR-book/html/htmledition/latent-semantic-indexing-1.html</link><dc:creator>bsc</dc:creator><dc:date>2017-04-11T08:59:23+02:00</dc:date><dc:subject>nlp textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Latent semantic indexing&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/nlp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://tidytextmining.com/index.html"><title>Tidy Text Mining with R</title><description></description><link>http://tidytextmining.com/index.html</link><dc:creator>alekos1</dc:creator><dc:date>2016-11-27T04:31:06+01:00</dc:date><dc:subject>NLP R TextMining </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-11-27T04:31:06+01:00&#034; href=&#034;http://tidytextmining.com/index.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://tidytextmining.com/index.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/NLP"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/R"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/TextMining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.textpresso.org/"><title>Textpresso: information extracting and processing for biological literature</title><description></description><link>http://www.textpresso.org/</link><dc:creator>danielle.dennie</dc:creator><dc:date>2016-05-26T22:27:59+02:00</dc:date><dc:subject>database bioinformatics textmining biology </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-05-26T22:27:59+02:00&#034; href=&#034;http://www.textpresso.org/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.textpresso.org/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/database"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bioinformatics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/biology"/></rdf:Bag></taxo:topics></item><item rdf:about="https://georeferenced.wordpress.com/2013/01/15/rwordcloud/"><title>How I used R to create a word cloud, step by step | Georeferenced</title><description></description><link>https://georeferenced.wordpress.com/2013/01/15/rwordcloud/</link><dc:creator>ans</dc:creator><dc:date>2015-06-03T11:42:15+02:00</dc:date><dc:subject>r textmining wordcloud </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2015-06-03T11:42:15+02:00&#034; href=&#034;https://georeferenced.wordpress.com/2013/01/15/rwordcloud/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://georeferenced.wordpress.com/2013/01/15/rwordcloud/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/r"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/wordcloud"/></rdf:Bag></taxo:topics></item><item rdf:about="http://contentmine.org/"><title>ContentMine</title><description>The ContentMine uses machines to liberate 100,000,000 facts from the scientific literature</description><link>http://contentmine.org/</link><dc:creator>jaj</dc:creator><dc:date>2015-06-01T17:20:27+02:00</dc:date><dc:subject>computational_analysis textmining tools </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;The ContentMine uses machines to liberate 100,000,000 facts from the scientific literature&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/computational_analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/></rdf:Bag></taxo:topics></item><item rdf:about="http://gisele.underarmour.com/"><title>Under Armour Women - I Will What I Want - Gisele Bündchen</title><description>Watch Gisele Bündchen stand with Under Armour in the face of real-time social commentary. Proving that she wills what she wants.</description><link>http://gisele.underarmour.com/</link><dc:creator>kw</dc:creator><dc:date>2015-01-20T16:49:44+01:00</dc:date><dc:subject>marketingcampain socialmedia textmining threejs visualisation webgl </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Watch Gisele Bündchen stand with Under Armour in the face of real-time social commentary. Proving that she wills what she wants.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/marketingcampain"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/socialmedia"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/threejs"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualisation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/webgl"/></rdf:Bag></taxo:topics></item><item rdf:about="https://jaibeermalik.wordpress.com/2013/03/26/elasticsearch-text-analysis-for-content-enrichment/"><title>ElasticSearch: Text analysis for content enrichment « Jai’s Weblog – Tech, Security &amp; Fun…</title><description>Every text search solution is as powerful as the text analysis capabilities it offers. Lucene is such open source information retrieval library offering many text analysis possibilities. In this post, we will cover some of the main text analysis features offered by ElasticSearch available to enrich your search content.</description><link>https://jaibeermalik.wordpress.com/2013/03/26/elasticsearch-text-analysis-for-content-enrichment/</link><dc:creator>kw</dc:creator><dc:date>2015-01-16T17:13:45+01:00</dc:date><dc:subject>analysis elasticsearch textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Every text search solution is as powerful as the text analysis capabilities it offers. Lucene is such open source information retrieval library offering many text analysis possibilities. In this post, we will cover some of the main text analysis features offered by ElasticSearch available to enrich your search content.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elasticsearch"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://blog.florian-hopf.de/2013/09/simple-event-analytics-with.html"><title>Dev Time: Simple Event Analytics with ElasticSearch and the Twitter River</title><description></description><link>http://blog.florian-hopf.de/2013/09/simple-event-analytics-with.html</link><dc:creator>kw</dc:creator><dc:date>2015-01-16T16:42:29+01:00</dc:date><dc:subject>elasticsearch eventdetection textmining </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2015-01-16T16:42:29+01:00&#034; href=&#034;http://blog.florian-hopf.de/2013/09/simple-event-analytics-with.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://blog.florian-hopf.de/2013/09/simple-event-analytics-with.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elasticsearch"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/eventdetection"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/spinscale/elasticsearch-opennlp-plugin"><title>spinscale/elasticsearch-opennlp-plugin · GitHub</title><description>elasticsearch-opennlp-plugin - Additional opennlp mapping type for elasticsearch in order to perform named entity recognition</description><link>https://github.com/spinscale/elasticsearch-opennlp-plugin</link><dc:creator>kw</dc:creator><dc:date>2015-01-16T16:24:24+01:00</dc:date><dc:subject>elasticsearch opennlp textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;elasticsearch-opennlp-plugin - Additional opennlp mapping type for elasticsearch in order to perform named entity recognition&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elasticsearch"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/opennlp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/pandastrike/bayzee"><title>pandastrike/bayzee · GitHub</title><description>bayzee - Text classification using Naive Bayes and Elasticsearch</description><link>https://github.com/pandastrike/bayzee</link><dc:creator>kw</dc:creator><dc:date>2015-01-16T16:19:35+01:00</dc:date><dc:subject>bayes classification elasticsearch textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;bayzee - Text classification using Naive Bayes and Elasticsearch&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elasticsearch"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/polyfractal/ElasticBayes"><title>polyfractal/ElasticBayes · GitHub</title><description>ElasticBayes - Naive Bayes Classifier implemented with Elasticsearch Aggregations</description><link>https://github.com/polyfractal/ElasticBayes</link><dc:creator>kw</dc:creator><dc:date>2015-01-16T16:14:41+01:00</dc:date><dc:subject>bayes classification elasticsearch textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;ElasticBayes - Naive Bayes Classifier implemented with Elasticsearch Aggregations&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elasticsearch"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://uima.apache.org/"><title>Apache UIMA - Apache UIMA</title><description></description><link>https://uima.apache.org/</link><dc:creator>kw</dc:creator><dc:date>2015-01-13T14:22:14+01:00</dc:date><dc:subject>analysis apache bigdata framework textmining </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2015-01-13T14:22:14+01:00&#034; href=&#034;https://uima.apache.org/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://uima.apache.org/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/apache"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bigdata"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/framework"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.newsreader-project.eu/"><title>NewsReader</title><description>Welcome to NewsReader: “Building structured event Indexes of large volumes of financial and economic Data for Decision Making”

The volume of news data is enormous and expanding, covering billions of archived documents with millions of documents added daily. These documents are also getting more and more interconnected with knowledge from other sources such as biographies and company databases.

Professional decision makers who need to respond quickly to new developments or who need to explain these developments on the basis of the past are faced with the problem that current solutions for consulting these archives no longer work.  There are simply too many possibly relevant and partially overlapping documents and from these documents decision makers still need to distinguish the correct from the wrong, the new from the old, the actual from the out-of-date by reading the content and maintaining a record in memory. Consequently, it becomes almost impossible to make well-informed decisions and professionals risk to be held liable for decisions based on incomplete, inaccurate and out-of-date information.

NewsReader will process news in 4 different languages when it comes in. It will extract what happened to whom, when and where, removing duplication, complementing information, registering inconsistencies and keeping track of the original sources. Any new information is integrated with the past, distinguishing the new from the old in an unfolding story line, similar to how people tend to remember the past and access knowledge and information. The difference here is  that NewsReader can provide access to all original sources and will not forget any details (like a “History Recorder”). We will develop a decision-support tool that allows professional decision makers to explore these story lines using visual interfaces and interactions to exploit their explanatory power and their systematic structural implications. Likewise, NewsReader can make predictions from the past on future events or explain new events and developments through the past.</description><link>http://www.newsreader-project.eu/</link><dc:creator>kw</dc:creator><dc:date>2015-01-13T13:26:29+01:00</dc:date><dc:subject>competitiveintelligence newsreader textmining </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Welcome to NewsReader: “Building structured event Indexes of large volumes of financial and economic Data for Decision Making”

The volume of news data is enormous and expanding, covering billions of archived documents with millions of documents added daily. These documents are also getting more and more interconnected with knowledge from other sources such as biographies and company databases.

Professional decision makers who need to respond quickly to new developments or who need to explain these developments on the basis of the past are faced with the problem that current solutions for consulting these archives no longer work.  There are simply too many possibly relevant and partially overlapping documents and from these documents decision makers still need to distinguish the correct from the wrong, the new from the old, the actual from the out-of-date by reading the content and maintaining a record in memory. Consequently, it becomes almost impossible to make well-informed decisions and professionals risk to be held liable for decisions based on incomplete, inaccurate and out-of-date information.

NewsReader will process news in 4 different languages when it comes in. It will extract what happened to whom, when and where, removing duplication, complementing information, registering inconsistencies and keeping track of the original sources. Any new information is integrated with the past, distinguishing the new from the old in an unfolding story line, similar to how people tend to remember the past and access knowledge and information. The difference here is  that NewsReader can provide access to all original sources and will not forget any details (like a “History Recorder”). We will develop a decision-support tool that allows professional decision makers to explore these story lines using visual interfaces and interactions to exploit their explanatory power and their systematic structural implications. Likewise, NewsReader can make predictions from the past on future events or explain new events and developments through the past.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/competitiveintelligence"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/newsreader"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="https://uima.apache.org/"><title>Apache UIMA - Apache UIMA</title><description></description><link>https://uima.apache.org/</link><dc:creator>asmelash</dc:creator><dc:date>2015-01-10T19:45:57+01:00</dc:date><dc:subject>framework textmining uima </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2015-01-10T19:45:57+01:00&#034; href=&#034;https://uima.apache.org/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://uima.apache.org/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/framework"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/uima"/></rdf:Bag></taxo:topics></item><item rdf:about="http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track"><title>ROSALIND | Problems</title><description></description><link>http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track</link><dc:creator>asmelash</dc:creator><dc:date>2014-07-14T20:36:07+02:00</dc:date><dc:subject>bioinformatics problemsolving programming stringprocessing textmining </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2014-07-14T20:36:07+02:00&#034; href=&#034;http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bioinformatics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/problemsolving"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/stringprocessing"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/textmining"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.r-bloggers.com/text-mining-in-r-automatic-categorization-of-wikipedia-articles/"><title>Text mining in R – Automatic categorization of Wikipedia articles | (R news &amp; tutorials)</title><description></description><link>http://www.r-bloggers.com/text-mining-in-r-automatic-categorization-of-wikipedia-articles/</link><dc:creator>marsianus</dc:creator><dc:date>2014-06-26T15:05:20+02:00</dc:date><dc:subject>GnuR TextMining Wikipedia </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2014-06-26T15:05:20+02:00&#034; href=&#034;http://www.r-bloggers.com/text-mining-in-r-automatic-categorization-of-wikipedia-articles/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.r-bloggers.com/text-mining-in-r-automatic-categorization-of-wikipedia-articles/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/GnuR"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/TextMining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Wikipedia"/></rdf:Bag></taxo:topics></item></rdf:RDF>