DocumentCode :
2539708
Title :
Topical Crawler based on multi-level vector space model and optimized hyperlink chosen strategy
Author :
Xu, Yang ; Ai-na, Sui ; Zhan-kun, Tang
Author_Institution :
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fYear :
2010
fDate :
7-9 July 2010
Firstpage :
430
Lastpage :
435
Abstract :
In this study, through researching and analyzing the technology of Topical Crawler, we improve the critical algorithm, and present the Topic-Relevance judgment algorithm based on Multi-Level Vector Space Model and the Topical Search Strategy based on the content evaluation, which combine with the simple link structure analysis and link tags data analysis. Through the analysis of the experimental data, the algorithm and the strategy proposed in this research have higher accuracy and efficiency, which can improve the performance of the Traditional Topical Crawler greatly.
Keywords :
Web services; data analysis; optimisation; query formulation; relevance feedback; data analysis; hyperlink chosen strategy; link tags; multi-level vector space model; optimisation; topic-relevance judgment algorithm; topical crawler; topical search strategy; Algorithm design and analysis; Analytical models; Computational modeling; Crawlers; Queueing analysis; Search engines; Web pages; Multi-Level Vector Space Model; Topic-Relevance; Topical Crawler; Topical Search Strategy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8041-8
Type :
conf
DOI :
10.1109/COGINF.2010.5599702
Filename :
5599702
Link To Document :
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