Text mining

Results: 892



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21Practice Questions for CS410 Midterm Exam Please feel free to discuss these questions with your classmates 1. Let M be the unigram language model representing the “text mining topic” shown on slide 22 of the NLP lect

Practice Questions for CS410 Midterm Exam Please feel free to discuss these questions with your classmates 1. Let M be the unigram language model representing the “text mining topic” shown on slide 22 of the NLP lect

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Source URL: sifaka.cs.uiuc.edu

- Date: 2014-04-10 17:07:22
    22Comparable Study of Event Extraction in Newswire and Biomedical Domains Makoto Miwa†,‡ Paul Thompson† Ioannis Korkontzelos† Sophia Ananiadou† † National Centre for Text Mining and School of Computer Science,

    Comparable Study of Event Extraction in Newswire and Biomedical Domains Makoto Miwa†,‡ Paul Thompson† Ioannis Korkontzelos† Sophia Ananiadou† † National Centre for Text Mining and School of Computer Science,

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    Source URL: www.aclweb.org

    - Date: 2014-08-08 12:26:28
      23Practice Questions for CS410 Midterm Exam Please feel free to discuss these questions with your classmates 1. Let M be the unigram language model representing the “text mining topic” shown on slide 22 of the NLP lect

      Practice Questions for CS410 Midterm Exam Please feel free to discuss these questions with your classmates 1. Let M be the unigram language model representing the “text mining topic” shown on slide 22 of the NLP lect

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      Source URL: sifaka.cs.uiuc.edu

      - Date: 2013-03-28 14:01:46
        24PhD Subject: Unsupervised Template Acquisition for Open Event Extraction Keywords: Natural Language Processing, Text Mining, Knowledge Extraction, Event Extraction, Unsupervised Learning Ideal starting date: JanDu

        PhD Subject: Unsupervised Template Acquisition for Open Event Extraction Keywords: Natural Language Processing, Text Mining, Knowledge Extraction, Event Extraction, Unsupervised Learning Ideal starting date: JanDu

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        Source URL: perso.limsi.fr

        - Date: 2016-06-09 03:02:09
          25Improving Text Mining with Controlled Natural Language: A Case Study for Protein Interactions Tobias Kuhn1,2 , Lo¨ıc Royer1, Norbert E. Fuchs2 , and Michael Schroeder1 1 Biotechnological Center, TU Dresden, Germany

          Improving Text Mining with Controlled Natural Language: A Case Study for Protein Interactions Tobias Kuhn1,2 , Lo¨ıc Royer1, Norbert E. Fuchs2 , and Michael Schroeder1 1 Biotechnological Center, TU Dresden, Germany

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          Source URL: attempto.ifi.uzh.ch

          - Date: 2013-09-23 06:46:42
            26Mining Quality Phrases from Massive Text Corpora Jialu Liu†∗ Jingbo Shang†∗ Chi Wang‡ † {jliu64, shang7, xren7, hanj}@illinois.edu

            Mining Quality Phrases from Massive Text Corpora Jialu Liu†∗ Jingbo Shang†∗ Chi Wang‡ † {jliu64, shang7, xren7, hanj}@illinois.edu

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            Source URL: hanj.cs.illinois.edu

            - Date: 2015-03-26 23:03:13
              27Text Mining für News-Sites Nina Hälker Department Informatik, HAW Hamburg Sommersemester 2014 Ablauf

              Text Mining für News-Sites Nina Hälker Department Informatik, HAW Hamburg Sommersemester 2014 Ablauf

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              Source URL: users.informatik.haw-hamburg.de

              - Date: 2014-05-28 03:43:04
                28Mining insights from text Improving Predictability of Oil via Reuters News Text Sameena Shah1, Armineh Nourbakhsh2 1 Director, Research and Head of R&D NY Labs, Thomson Reuters 2

                Mining insights from text Improving Predictability of Oil via Reuters News Text Sameena Shah1, Armineh Nourbakhsh2 1 Director, Research and Head of R&D NY Labs, Thomson Reuters 2

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                Source URL: fpq.io

                - Date: 2016-05-13 23:11:45
                  29Melting point prediction using large data sets made possible by text mining Daniel 1NextMove 1

                  Melting point prediction using large data sets made possible by text mining Daniel 1NextMove 1

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                  Source URL: cisrg.shef.ac.uk

                  - Date: 2016-07-11 10:18:11
                    30Text Mining with RapidMiner Text Mining with RapidMiner Course Overview Text Mining with RapidMiner is a one day course and is an introduction into knowledge knowledge discovery using

                    Text Mining with RapidMiner Text Mining with RapidMiner Course Overview Text Mining with RapidMiner is a one day course and is an introduction into knowledge knowledge discovery using

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                    Source URL: 1xltkxylmzx3z8gd647akcdvov-wpengine.netdna-ssl.com

                    - Date: 2016-07-08 15:11:45