Details
| Original language | English |
|---|---|
| Title of host publication | SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Pages | 331-338 |
| Number of pages | 8 |
| Publication status | Published - 9 Jul 2010 |
| Event | 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 - Geneva, Switzerland Duration: 19 Jul 2010 → 23 Jul 2010 |
Publication series
| Name | SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
|---|
Abstract
Keyword queries over structured databases are notoriously ambiguous. No single interpretation of a keyword query can satisfy all users, and multiple interpretations may yield overlapping results. This paper proposes a scheme to balance the relevance and novelty of keyword search results over structured databases. Firstly, we present a probabilistic model which effectively ranks the possible interpretations of a keyword query over structured data. Then, we introduce a scheme to diversify the search results by re-ranking query interpretations, taking into account redundancy of query results. Finally, we propose α-nDCG-W and WS-recall, an adaptation of α-nDCG and S-recall metrics, taking into account graded relevance of subtopics. Our evaluation on two real-world datasets demonstrates that search results obtained using the proposed diversification algorithms better characterize possible answers available in the database than the results of the initial relevance ranking.
Keywords
- Diversity, Query intent, Ranking in databases
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
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SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 2010. p. 331-338 (SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - DivQ
T2 - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010
AU - Demidova, Elena
AU - Fankhauser, Peter
AU - Zhou, Xuan
AU - Nejdl, Wolfgang
PY - 2010/7/9
Y1 - 2010/7/9
N2 - Keyword queries over structured databases are notoriously ambiguous. No single interpretation of a keyword query can satisfy all users, and multiple interpretations may yield overlapping results. This paper proposes a scheme to balance the relevance and novelty of keyword search results over structured databases. Firstly, we present a probabilistic model which effectively ranks the possible interpretations of a keyword query over structured data. Then, we introduce a scheme to diversify the search results by re-ranking query interpretations, taking into account redundancy of query results. Finally, we propose α-nDCG-W and WS-recall, an adaptation of α-nDCG and S-recall metrics, taking into account graded relevance of subtopics. Our evaluation on two real-world datasets demonstrates that search results obtained using the proposed diversification algorithms better characterize possible answers available in the database than the results of the initial relevance ranking.
AB - Keyword queries over structured databases are notoriously ambiguous. No single interpretation of a keyword query can satisfy all users, and multiple interpretations may yield overlapping results. This paper proposes a scheme to balance the relevance and novelty of keyword search results over structured databases. Firstly, we present a probabilistic model which effectively ranks the possible interpretations of a keyword query over structured data. Then, we introduce a scheme to diversify the search results by re-ranking query interpretations, taking into account redundancy of query results. Finally, we propose α-nDCG-W and WS-recall, an adaptation of α-nDCG and S-recall metrics, taking into account graded relevance of subtopics. Our evaluation on two real-world datasets demonstrates that search results obtained using the proposed diversification algorithms better characterize possible answers available in the database than the results of the initial relevance ranking.
KW - Diversity
KW - Query intent
KW - Ranking in databases
UR - http://www.scopus.com/inward/record.url?scp=77956014301&partnerID=8YFLogxK
U2 - 10.1145/1835449.1835506
DO - 10.1145/1835449.1835506
M3 - Conference contribution
AN - SCOPUS:77956014301
SN - 9781605588964
T3 - SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 331
EP - 338
BT - SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Y2 - 19 July 2010 through 23 July 2010
ER -