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  Browse All Reviews > Information Systems (H) > Information Storage And Retrieval (H.3) > Content Analysis And Indexing (H.3.1) > Linguistic Processing (H.3.1...)  
 
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  1-10 of 27 Reviews about "Linguistic Processing (H.3.1...)": Date Reviewed
  Text data management and analysis: a practical introduction to information retrieval and text mining
Zhai C., Massung S., Association for Computing Machinery and Morgan & Claypool, New York, NY, 2016. 530 pp.  Type: Book, Reviews: (4 of 4)

Zhai and Massung’s new book Text data management and analysis provides a fresh new look at the areas of text retrieval, text mining, and text management. Traditionally, these three areas are separate, each with a rich ...

Nov 14 2016
  Text data management and analysis: a practical introduction to information retrieval and text mining
Zhai C., Massung S., Association for Computing Machinery and Morgan & Claypool, New York, NY, 2016. 530 pp.  Type: Book, Reviews: (3 of 4)

Fifteen years ago, the field of information retrieval (IR) was still in its infancy, despite the fact that research and development in the field had been progressing for over 30 years, and had provided several significant advances. The...

Nov 11 2016
   Text data management and analysis: a practical introduction to information retrieval and text mining
Zhai C., Massung S., Association for Computing Machinery and Morgan & Claypool, New York, NY, 2016. 530 pp.  Type: Book, Reviews: (2 of 4)

An old rule of thumb suggests that 90 percent of all potentially relevant business information is in unstructured form. Hence, it is no surprise that many mathematically ill-defined problems associated with text analysis have attracted...

Oct 17 2016
  Text data management and analysis: a practical introduction to information retrieval and text mining
Zhai C., Massung S., Association for Computing Machinery and Morgan & Claypool, New York, NY, 2016. 530 pp.  Type: Book, Reviews: (1 of 4)

One of the most rapidly growing sources of data, natural-language text, is also one of the most difficult to analyze. Computerized understanding of natural language was among the earliest anticipated benefits of artificial intelligence...

Oct 12 2016
  Sentiment analysis tools should take account of the number of exclamation marks!!!
Teh P., Rayson P., Pak I., Piao S.  iiWAS 2015 (Proceedings of the 17th International Conference on Information Integration and Web-based Applications & Services, Brussels, Belgium, Dec 11-13, 2015) 1-6, 2015.  Type: Proceedings

Is it a good idea to have a spam filter rule that rejects messages containing more than one exclamation mark in the subject line? This paper considers the authorial sentiments ascribed to communications containing one or more exclamati...

Jun 7 2016
  Sentiment analysis in medical settings
Denecke K., Deng Y. Artificial Intelligence in Medicine 64(1): 17-27, 2015.  Type: Article

Most diagnosis and medical decision-making processes for the purpose of treatments are commonly based on the recorded medical sentiments from an earlier treatment stage. These medical sentiments are in turn based on patient (subjective...

Nov 11 2015
  Learning to rank answers to non-factoid questions from Web collections
Surdeanu M., Ciaramita M., Zaragoza H. Computational Linguistics 37(2): 351-383, 2011.  Type: Article

Typical question-answering (QA) system answers to factoid questions are usually no longer than two words. However, to be matched correctly to relevant digital documents on the Web, the answers must be very precise--they must c...

Jan 19 2012
  Using topic themes for multi-document summarization
Harabagiu S., Lacatusu F. ACM Transactions on Information Systems 28(3): 1-47, 2010.  Type: Article

With the increase of digital text and the rise of related metadata, there is a growing interest in finding ways to reduce information overload while still maintaining the most important and useful content. Focused multi-document summar...

Nov 22 2010
   A comparison of human and computer marking of short free-text student responses
Butcher P., Jordan S. Computers & Education 55(2): 489-499, 2010.  Type: Article

Are computer-assisted assessment (CAA) systems as capable as human instructors of competently evaluating and grading sentence-length responses in written tests? If so, what depth of natural language processing is required? Based on a b...

Oct 26 2010
  Improving the extraction of bilingual terminology from Wikipedia
Erdmann M., Nakayama K., Hara T., Nishio S. ACM Transactions on Multimedia Computing, Communications, and Applications 5(4): 1-17, 2009.  Type: Article

Wikipedia is presumably the most popular encyclopedia on the Net. It is maintained by users who are not necessarily specialists in the respective fields, so the quality of the knowledge presented is not always reliable. On the other ha...

Mar 12 2010
 
 
 
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