Please use this identifier to cite or link to this item: http://dspace.dtu.ac.in:8080/jspui/handle/123456789/249
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dc.contributor.authorTRIPATHI, VIVEK-
dc.date.accessioned2010-11-09T06:25:55Z-
dc.date.available2010-11-09T06:25:55Z-
dc.date.issued2009-07-06-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/123456789/249-
dc.descriptionME THESISen_US
dc.description.abstractText mining, also known as text data mining or knowledge discovery from textual databases refers to the process of extracting interesting and non-trivial patterns or knowledge from unstructured text documents from a fixed domain. Text Mining tasks include text categorization, text clustering, concept/entity extraction, document summarization, and entity relation modeling. In this work, the focus is given to concept/entity extraction only. The major challenging issue in extracting concept/entity from texts is natural language words are always ambiguous. Up to now, not much research in text mining especially in concept/entity extraction has focused on the ambiguity problem. Ambiguity problem occur when a sentence could be interpreted in more than one meaning here we addresses ambiguity issues in natural language texts, and presents a new technique for resolving ambiguity problem in extracting concept/entity from texts. The approach is developed by utilizing natural language processin...en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD-535;45-
dc.subjectText Miningen_US
dc.subjectLexical Ambiguityen_US
dc.titleAN APPROACH TO REMOVE LEXICAL AMBIGUITY IN TEXT MININGen_US
Appears in Collections:M.E./M.Tech. Computer Technology & Applications

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