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| Category | Value | ||
| Available via | http://dbpubs.stanford.edu/pub/2003-29 | ||
| Previous version | 2002-6 | ||
| Submitted on | 17th of May 2003 | ||
| Author | Haveliwala, Taher H. | ||
| Title | Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search | ||
| Date of publication | 2003 | ||
| Published in | IEEE Transactions on Knowledge and Data Engineering | ||
| Citation | Haveliwala, Taher H.. Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search, IEEE Transactions on Knowledge and Data Engineering, 2003. | ||
| Number of pages | 22 | ||
| Language | English | ||
| Project | Stanford InfoLab; Database Group | ||
| Type | Conference or Journal Paper | ||
| Subject group | Computer Science | ||
| Abstract | The original PageRank algorithm for improving the ranking of search-query results computes a single vector, using the link structure of the Web, to capture the relative ``importance'' of Web pages, independent of any particular search query. To yield more accurate search results, we propose computing a {\em set} of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic. For ordinary keyword search queries, we compute the topic-sensitive PageRank scores for pages satisfying the query using the topic of the query keywords. For searches done in context (e.g., when the search query is performed by highlighting words in a Web page), we compute the topic-sensitive PageRank scores using the topic of the context in which the query appeared. By using linear combinations of these (precomputed) biased PageRank vectors to generate context-specific importance scores for pages at query time, we show that we can generate more accurate rankings than with a single, generic PageRank vector. | ||
| Keywords | PageRank, link analysis, web search | ||
| Contact address | taherh@cs.stanford.edu | ||
| Sponsored by | This work was done with the support of NSF Grant IIS-0085896 and an NSF Graduate Research Fellowship. | ||
| Notes | Extended version of the WWW2002 paper on Topic-Sensitive PageRank. | ||
| Fulltext source |
| Management of the document by | siroker@db.stanford.edu
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