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1
Word sense disambiguation: a survey
In: http://www.dsi.uniroma1.it/~navigli/pubs/ACM_Survey_2009_Navigli.pdf (2009)
Abstract: Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.
Keyword: Algorithms; Categories and Subject Descriptors; Experimentation; I.2.4 [Artificial Intelligence; I.2.7 [Artificial Intelligence; Knowledge Representation Formalisms and Methods General Terms; lexical ambiguity; lexical semantics; Measurement; Natural Language Processing—Text analysis; Performance Additional Key Words and Phrases; semantic annotation ACM Reference Format; sense annotation; Word sense disambiguation; word sense discrimination; WSD
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.8457
http://www.dsi.uniroma1.it/~navigli/pubs/ACM_Survey_2009_Navigli.pdf
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2
Textual Analysis of Stock Market Prediction Using Financial News Articles
In: http://www.robschumaker.com/publications/ACM TOIS - Textual Analysis of Stock Market Prediction Using Financial News Articles.pdf (2006)
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3
Meaningful term extraction and discriminative term selection in text categorization via unknown-word methodology
In: http://www.cs.toronto.edu/~gh/Courses/2528/Readings/2002f/Lai+Wu.pdf (2002)
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