Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 7-14 |
| Number of pages | 8 |
| ISBN (print) | 1595935975, 9781595935977 |
| Publication status | Published - 23 Jul 2007 |
| Event | 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 - Amsterdam, Netherlands Duration: 23 Jul 2007 → 27 Jul 2007 |
Abstract
The inherent ambiguity of short keyword queries demands for enhanced methods for Web retrieval. In this paper we propose to improve such Web queries by expanding them with terms collected from each user's Personal Information Repository, thus implicitly personalizing the search output. We introduce five broad techniques for generating the additional query keywords by analyzing user data at increasing granularity levels, ranging from term and compound level analysis up to global co-occurrence statistics, as well as to using external thesauri. Our extensive empirical analysis under four different scenarios shows some of these approaches to perform very well, especially on ambiguous queries, producing a very strong increase in the quality of the output rankings. Subsequently, we move this personalized search framework one step further and propose to make the expansion process adaptive to various features of each query. A separate set of experiments indicates the adaptive algorithms to bring an additional statistically significant improvement over the best static expansion approach.
Keywords
- Desktop profile, Keyword co-occurrences, Keyword extraction, Personalized web search, Query expansion
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Software
- Mathematics(all)
- Applied Mathematics
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Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07. Association for Computing Machinery (ACM), 2007. p. 7-14.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Personalized query expansion for the web
AU - Chirita, Paul Alexandru
AU - Firan, Claudiu S.
AU - Nejdl, Wolfgang
PY - 2007/7/23
Y1 - 2007/7/23
N2 - The inherent ambiguity of short keyword queries demands for enhanced methods for Web retrieval. In this paper we propose to improve such Web queries by expanding them with terms collected from each user's Personal Information Repository, thus implicitly personalizing the search output. We introduce five broad techniques for generating the additional query keywords by analyzing user data at increasing granularity levels, ranging from term and compound level analysis up to global co-occurrence statistics, as well as to using external thesauri. Our extensive empirical analysis under four different scenarios shows some of these approaches to perform very well, especially on ambiguous queries, producing a very strong increase in the quality of the output rankings. Subsequently, we move this personalized search framework one step further and propose to make the expansion process adaptive to various features of each query. A separate set of experiments indicates the adaptive algorithms to bring an additional statistically significant improvement over the best static expansion approach.
AB - The inherent ambiguity of short keyword queries demands for enhanced methods for Web retrieval. In this paper we propose to improve such Web queries by expanding them with terms collected from each user's Personal Information Repository, thus implicitly personalizing the search output. We introduce five broad techniques for generating the additional query keywords by analyzing user data at increasing granularity levels, ranging from term and compound level analysis up to global co-occurrence statistics, as well as to using external thesauri. Our extensive empirical analysis under four different scenarios shows some of these approaches to perform very well, especially on ambiguous queries, producing a very strong increase in the quality of the output rankings. Subsequently, we move this personalized search framework one step further and propose to make the expansion process adaptive to various features of each query. A separate set of experiments indicates the adaptive algorithms to bring an additional statistically significant improvement over the best static expansion approach.
KW - Desktop profile
KW - Keyword co-occurrences
KW - Keyword extraction
KW - Personalized web search
KW - Query expansion
UR - http://www.scopus.com/inward/record.url?scp=36448996579&partnerID=8YFLogxK
U2 - 10.1145/1277741.1277746
DO - 10.1145/1277741.1277746
M3 - Conference contribution
AN - SCOPUS:36448996579
SN - 1595935975
SN - 9781595935977
SP - 7
EP - 14
BT - Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
PB - Association for Computing Machinery (ACM)
T2 - 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
Y2 - 23 July 2007 through 27 July 2007
ER -