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
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;
Conference_Titel :
Commerce and Enterprise Computing (CEC), 2012 IEEE 14th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-6246-7
DOI :
10.1109/CEC.2012.40