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Towards High-Performance Word Sense Disambiguation

 

Marketed By :  AV Akademikerverlag   Sold By :  Kamal Books International  
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  • Product Description
 

Revision with unchanged content. Supervised word sense disambiguation (WSD) for truly polysemous words (in contrast to homonyms) is difficult for machine learning, mainly due to two problems: the lack of sense-tagged training data and the sparsity of the matrix of observed instances vs. features. At the same time, high accuracy is necessary for WSD to be beneficial for high-level applications, such as information retrieval, question answering, and machine translation. This work addresses the above two problems through combining rich linguistic knowledge and machine learning methods. First, it proposes and demonstrates empirically evidence that careful design and generation of linguistically motivated features help to alleviate the data sparseness inherent in WSD. A state-of-the-art supervised system for verb sense disambiguation was introduced. Exploration in three specific aspects of feature generation was discussed and shown to elevate the system accuracy to top-level. It also shows the effectiveness of active learning in the creation of more labeled training data for supervised WSD – reducing the required training data by 1/2 to 3/4 when learning coarse-grained English verb senses. The book is addressed to researchers in Computer and Information Science and Computational Linguistics.

Product Specifications
SKU :COC18135
AuthorXinbing Wang
LanguageEnglish
BindingPaperback
Number of Pages184
Publishing Year5/28/2012
ISBN978-3639387353
Edition1 st
Book TypeComputer networking & communications
Country of ManufactureIndia
Product BrandAV Akademikerverlag
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-27 00:00:00