Research on information measurement at semantic level

Authors:
Kaizhong Jiang;Lu Li;Bosheng Xu
Affiliations:
College of Basic Teaching, Shanghai University of Engineering Science, Shanghai, China;College of Basic Teaching, Shanghai University of Engineering Science, Shanghai, China;College of Basic Teaching, Shanghai University of Engineering Science, Shanghai, China
Venue:
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Year:
2011

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Foundations of statistical natural language processing

Foundations of statistical natural language processing
Probabilistic latent semantic indexing

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval

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Abstract

The paper defined an information measure associated with a topic or semantics for a keyword based corpus. Firstly, the topic-based corpus was obtained. Then the latent semantic vector space model of the corpus was established. After that, the information measure of the keyword was defined through the vector space model. Accordingly, it could be calculated that the amount of the topic information any document contained. Lastly, the membership degree which measured the degree of membership of the document belonging to the topic was introduced. Set a measurement threshold, thereby it was determined whether the documents belonging to the topic or not. Experiments show that the definition of the information measurement can get over the difficulty of the word-match search and real reach the goal of the Semantic-match search.