CLBCRA-Approach for Combination of Content-Based and Link-Based Ranking in Web Search

Authors:
Hao-Ming Wang;Ye Guo
Affiliations:
Department of Computer Science, Xi'an University of Finance & Economics, Xi'an, Shaanxi 710061, P.R. China;Department of Computer Science, Xi'an University of Finance & Economics, Xi'an, Shaanxi 710061, P.R. China
Venue:
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Year:
2007

Citing 10
Cited 0

The anatomy of a large-scale hypertextual Web search engine

WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment

Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Cross-Lingual Document Similarity Calculation Using the Multilingual Thesaurus EUROVOC

CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Enhanced web document summarization using hyperlinks

Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Opportunities from Open Source Search

WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Improvement in TF-IDF scheme for Web pages based on the contents of their hyperlinked neighboring pages

Systems and Computers in Japan
Complex queries over web repositories

VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Combating web spam with trustrank

VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Beyond TFIDF weighting for text categorization in the vector space model

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A peer-to-peer architecture for information retrieval across digital library collections

ECDL'06 Proceedings of the 10th European conference on Research and Advanced Technology for Digital Libraries

Quantified Score

Hi-index	0.03

Visualization

Abstract

There were two kinds of methods in information retrieval, based on content and based on hyper-link. The quantity of computation in systems based on content was very large and the precision in systems based on hyper-link only was not ideal. It was necessary to develop a technique combining the advantages of two systems. In this paper, we drew up a framework by using the two methods. We set up the transition probability matrix, which composed of link information and the relevant value of pages with the given query. The relevant value was denoted by TFIDF. We got the CLBCRA by solving the equation with the coefficient of transition probability matrix. Experimental results showed that more pages, which were important both in content and hyper-link, were selected.