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  Browse All Reviews > Computing Methodologies (I) > Artificial Intelligence (I.2) > Natural Language Processing (I.2.7) > Text Analysis (I.2.7...)  
  1-10 of 40 Reviews about "Text Analysis (I.2.7...)": Date Reviewed
  Aspect extraction in sentiment analysis: comparative analysis and survey
Rana T., Cheah Y. Artificial Intelligence Review 46(4): 459-483, 2016.  Type: Article

This paper covers a considerable volume of research work in the area of sentiment analysis. The authors define sentiment analysis as the computational classification of the context of a user’s feelings within a passage of tex...

Mar 23 2017
  Towards automatic identification of core concepts in educational resources
Sultan M., Bethard S., Sumner T.  JCDL 2014 (Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries, London, UK, Sep 8-12, 2014) 379-388, 2014.  Type: Proceedings

This paper studies the problem of recognizing the degree of similarity between ideas expressed in sentences. In particular, the authors consider the case of science education, where a set of core ideas expressed in sentences exists and...

May 27 2015
  A platform for language independent summarization
Cabral L., Lins R., Mello R., Freitas F., Ávila B., Simske S., Riss M.  DocEng 2014 (Proceedings of the 2014 ACM Symposium on Document Engineering, Fort Collins, CO, Sep 16-19, 2014) 203-206, 2014.  Type: Proceedings

This paper describes a language independent, automatic text summarization system, the platform for language independent summarization (PLIS). Traditional text summarization systems mainly focus on the processing of English text. PLIS i...

Nov 4 2014
  Normalization of informal text
Pennell D., Liu Y. Computer Speech and Language 28(1): 256-277, 2014.  Type: Article

This detailed and well-written paper presents a study on the normalization of informal text. The idea of normalization is to convert or correct informal language use into its formal equivalent. An example would be the expansion of the ...

May 9 2014
   Unsupervised information extraction by text segmentation
Cortez E., da Silva A., Springer Publishing Company, Incorporated, New York, NY, 2013. 124 pp.  Type: Book (978-3-319025-96-4)

The typical result from a web search is still a ranked list of documents that may contain the information you’re looking for, but it is up to the user to actually extract the sought-after information. In order for search engi...

Apr 22 2014
  Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importance
Abdalgader K., Skabar A. ACM Transactions on Speech and Language Processing (TSLP) 9(1): 1-21, 2012.  Type: Article

One of the major challenges for computers remains the ability to deal with text formulated in a natural language. While significant advances in computational linguistics, artificial intelligence, computing power, and other aspects have...

Aug 24 2012
  Who wrote what where: analyzing the content of human and automatic summaries
Owczarzak K., Dang H.  WASDGML 11 (Proceedings of the Workshop on Automatic Summarization for Different Genres, Media, and Languages, Portland, OR, Jun 23, 2011) 25-32, 2011.  Type: Proceedings

Text summarization remains an elusive goal of automatic summarizers. The state of the art for summarization has begun to reach a limit using extractive techniques. Thus, systems have been given a new task of creating a more responsive ...

Mar 12 2012
  Learning to identify educational materials
Hassan S., Mihalcea R. ACM Transactions on Speech and Language Processing (TSLP) 8(2): 1-18, 2011.  Type: Article

Users often receive search results that are not accurate or consistent with their expectations. In this paper, the authors address the challenge of automating document identification, focusing on user needs. Their method improves the s...

Feb 6 2012
  Ontology-driven discovery of geospatial evidence in Web pages
Borges K., Davis, Jr. C., Laender A., Medeiros C. Geoinformatica 15(4): 609-631, 2011.  Type: Article

The ability to correctly interpret geospatial information is undoubtedly a difficult exercise for artificial intelligence. While humans easily deal with this problem, it is an enormous challenge for computers. The importance of this pr...

Dec 22 2011
  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 statement...

Jun 7 2011
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