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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 65 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 collection of re...

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. Then, following...

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 a lot of at...

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 (AI), but i...

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 exclamation marks, an...

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) narration ...

Nov 11 2015
  TORC: test plan optimization by requirements clustering
Güldali B., Funke H., Sauer S., Engels G.  Software Quality Journal 19(4): 771-799, 2011. Type: Article

The acceptance testing of large software systems is difficult and time-consuming because of the sheer volume of user requirements, especially when numerous users and service providers are involved. In this paper, the authors present an automatic a...

May 22 2012
  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 contain the same ...

Jan 19 2012
  Identification of fraudulent financial statements using linguistic credibility analysis
Humpherys S., Moffitt K., Burns M., Burgoon J., Felix W.  Decision Support Systems 50(3): 585-594, 2011. Type: Article

The Securities and Exchange Commission (SEC) requires publicly traded companies to file an annual report (10-K) that includes an overview of a company’s business and financial condition, as well as audited financial statements. These annual ...

Jun 7 2011
  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 summarization (MDS...

Nov 22 2010
 
 
 
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