DocumentCode
2989120
Title
An improved topic relevance algorithm for vertical search engines
Author
Lv, Lin-tao ; Chen, Li-ping ; Zhou, Hong-fang
Author_Institution
Inst. of Comput. Sci. & Eng., Xian Univ. of Technol., Xian
Volume
2
fYear
2008
fDate
30-31 Aug. 2008
Firstpage
753
Lastpage
757
Abstract
HITS algorithm is a famous topic distillation algorithm, but it has a drawback of topic drift. To tackle this problem, a new improved HITS algorithm is proposed by assigning appropriate weights to links according to the link value and topic similarity. Based on an analysis of web link structure, link value is calculated by web page authority degree; topic similarity of web pages is calculated by combining analysis of page content with HTML structure characteristics. Improved HITS algorithm combining link value with topic similarity highlights the difference of links and it assigns different weights to different links. Experiment results indicate that the proposed HITS algorithm can improve the relevance ratio by 13%-42%. Furthermore it can well control topic drift and enhance the accuracy of information collection. The proposed HITS algorithm can be applied in vertical search engines. It lays an important theoretical foundation for vertical search engines.
Keywords
Web sites; hypermedia markup languages; relevance feedback; search engines; HITS algorithm; HTML structure characteristics; Web link structure; Web pages; hyperlink induced topic search; improved topic relevance algorithm; vertical search engines; Algorithm design and analysis; Computer science; Electronic mail; HTML; Information resources; Pattern analysis; Pattern recognition; Search engines; Wavelet analysis; Web pages; HITS; Hyperlink; Link Value; Topic Drift; Topic Similarity;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-2238-8
Electronic_ISBN
978-1-4244-2239-5
Type
conf
DOI
10.1109/ICWAPR.2008.4635878
Filename
4635878
Link To Document