DocumentCode :
3180818
Title :
Measuring semantic similarity using web search engine
Author :
Shanmugapriya ; Latha, K.
Author_Institution :
Regional Centre, Anna Univ., Tiruchirapalli, India
fYear :
2013
fDate :
24-26 July 2013
Firstpage :
639
Lastpage :
644
Abstract :
An automatic method to measure semantic similarity between entities using web search engine which uses both page count and lexical patterns extracted from snippets. Semantic similarity is measured using both page count and lexical patterns based on snippets from web search engine for given query words. By using page count value, four word co-occurrence measures are calculated. Lexical patterns describing semantic relations are extracted from snippets returned by search engine. These patterns are then clustered using sequential algorithm. Word co-occurrence measures are combined with lexical patterns which is learned using SVM.
Keywords :
Internet; learning (artificial intelligence); pattern clustering; query processing; search engines; support vector machines; SVM; Web search engine; automatic method; learning; lexical patterns; page count value; pattern clustering; query words; semantic relation extraction; semantic similarity measurement; sequential algorithm; snippets; word co-occurrence measures; Automobiles; Computers; Engines; Lexical pattern clustering; Lexical pattern extraction; Page count; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Nanomaterials and Emerging Engineering Technologies (ICANMEET), 2013 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-1377-0
Type :
conf
DOI :
10.1109/ICANMEET.2013.6609373
Filename :
6609373
Link To Document :
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