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Naive Bayes Model for Unsupervised Word Sense Disambiguation : Aspects Concer...
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eBay item number:196314349223
Item specifics
- Condition
- Book Title
- Naive Bayes Model for Unsupervised Word Sense Disambiguation : As
- ISBN
- 9783642336928
- Publication Name
- The Naive Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection
- Publisher
- Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG
- Subject
- Computer Science, Mathematics
- Publication Year
- 2012
- Series
- Springerbriefs in Statistics
- Type
- Textbook
- Format
- Paperback
- Language
- English
- Item Height
- 235 mm
- Item Weight
- 1416 g
- Item Width
- 155 mm
- Number of Pages
- 70 Pages
About this product
Product Information
This book presents recent advances (from 2008 to 2012) concerning use of the Naive Bayes model in unsupervised word sense disambiguation (WSD). While WSD, in general, has a number of important applications in various fields of artificial intelligence (information retrieval, text processing, machine translation, message understanding, man-machine communication etc.), unsupervised WSD is considered important because it is language-independent and does not require previously annotated corpora. The Naive Bayes model has been widely used in supervised WSD, but its use in unsupervised WSD has led to more modest disambiguation results and has been less frequent. It seems that the potential of this statistical model with respect to unsupervised WSD continues to remain insufficiently explored. The present book contends that the Naive Bayes model needs to be fed knowledge in order to perform well as a clustering technique for unsupervised WSD and examines three entirely different sources of such knowledge for feature selection: WordNet, dependency relations and web N-grams. WSD with an underlying Naive Bayes model is ultimately positioned on the border between unsupervised and knowledge-based techniques. The benefits of feeding knowledge (of various natures) to a knowledge-lean algorithm for unsupervised WSD that uses the Naive Bayes model as clustering technique are clearly highlighted. The discussion shows that the Naive Bayes model still holds promise for the open problem of unsupervised WSD.
Product Identifiers
Publisher
Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG
ISBN-13
9783642336928
eBay Product ID (ePID)
138651017
Product Key Features
Number of Pages
70 Pages
Language
English
Publication Name
The Naive Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection
Publication Year
2012
Subject
Computer Science, Mathematics
Type
Textbook
Series
Springerbriefs in Statistics
Format
Paperback
Dimensions
Item Height
235 mm
Item Weight
1416 g
Item Width
155 mm
Additional Product Features
Country/Region of Manufacture
Germany
Item description from the seller
Business seller information
Value Added Tax Number:
- GB 307932304
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