DocumentCode :
599314
Title :
Extraction of Feature Words with the Same Generality Level as Query using Restricted Bootstrapping
Author :
Jun Zeng ; Sakai, Tadashi ; Flanagan, Brendan ; Hirokawa, Sachio
Author_Institution :
Grad. Sch. of Inf. Sci., Kyushu Univ., Fukuoka, Japan
fYear :
2012
fDate :
9-11 Sept. 2012
Firstpage :
171
Lastpage :
176
Abstract :
It is not so simple to get an appropriated level of search result among a large number of targets which might be too general or too specific. Hints for the query are valuable for a user to expand or shrink his next search step, if the hints would be shown with their levels compared with the user´s original query. This paper proposes a method to extract feature words of the same level as user´s query using restricted bootstrap. Examples are shown to demonstrate the effectiveness of the method on tourism blogs. The paper proposes an evaluation measure for the similarity of levels for words based on WordNet.
Keywords :
Web sites; query processing; statistical analysis; WordNet; feature words extraction; query generality level; restricted bootstrapping; similarity evaluation measure; tourism blog; user query; Blogs; Data mining; Educational institutions; Feature extraction; Search engines; Semantics; Web pages; Bootstrapping; Feature Extraction; WordNet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Commerce and Enterprise Computing (CEC), 2012 IEEE 14th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-6246-7
Type :
conf
DOI :
10.1109/CEC.2012.40
Filename :
6470797
Link To Document :
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