Feature Based Opinion Summarization using Transfer Learning : Research Perspective

Language: English

Published by LAP Lambert Academic Publishing, 2015

3659717940 / 9783659717949

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Opinion mining is used to improve the decision making of new user in various domains such as product, movie, news media, social networking shares etc. Feature based opinion mining rely only on single domain corpus in most of the existing methodology. Feature based opinion mining in two different domain corpuses is complex. The features and Opinion words are extracted with the help of the Part-of-Speech (PoS) tagging tool. The Inter dependent domain relevance (IDDR) technique use removal of redundant features and pruning of irrelevant features from two different domains with the help of the IDDR score and threshold value. Normally data mining and machine learning use training and test data from same domain and have same feature. But the above concept is not hold in all domains due to the lack of labeled dataset. Here the proposed transfer learning method using Exaggerate Instance weighted K nearest neighbor (EIWKNN) algorithm to transfer the knowledge from camera domain to iPod domain for Opinion classification. The summary of two different domains feature with respect to their opinion is generated.

Seller Inventory # 9783659717949

Title
Feature Based Opinion Summarization using Transfer Learning : Research Perspective
Author
Abirami Ragupathi
Publisher
LAP Lambert Academic Publishing
Publication year
2015
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659717940
ISBN 13
9783659717949
Item weight
149 grams
Dimensions
220x150x6 mm

AHA-BUCH GmbH

Einbeck, Germany

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AbeBooks seller since August 14, 2006

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