Name
Abstract | ||
|---|---|---|
The performance of web search engines may often deteriorate due to the diversity and noise contained within web pages. Some methods proposed to use clickthrough data to achieve more accurate information for web pages as well as improve the search performance. However, sparseness became the great challenge in exploiting clickthrough data. In this paper, we propose a novel algorithm to exploit the user clickthrough data. It first explores the relationship between queries and web pages to mine out co-visiting as the associative relationship among the Web pages, and then Spreading Activation mechanism is used to re-rank the results of Web search. Our approach could alleviate such sparseness and the experimental results on a large set of MSN clickthrough log data show a significant improvement on search performance over the DirectHit algorithm as well as the baseline search engine. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/978-3-540-31865-1_34 | ECIR |
Keywords | Field | DocType |
directhit algorithm,web page,web search,search performance,clickthrough data,associative relationship,msn clickthrough log data,user clickthrough data,web search engine,baseline search engine,web pages,search engine,spreading activation | Web search query,Data mining,Search engine,Web page,Query expansion,Information retrieval,Computer science,Exploit,Anchor text,Bibliographic coupling,The Internet | Conference |
Volume | ISSN | ISBN |
3408 | 0302-9743 | 3-540-25295-9 |
Citations | PageRank | References |
4 | 0.44 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xue-Mei Jiang | 1 | 25 | 4.03 |
| Wen-Guan Song | 2 | 18 | 1.80 |
| Hua-Jun Zeng | 3 | 1999 | 100.54 |