Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Seiten | 331-338 |
| Seitenumfang | 8 |
| Publikationsstatus | Veröffentlicht - 9 Juli 2010 |
| Veranstaltung | 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 - Geneva, Schweiz Dauer: 19 Juli 2010 → 23 Juli 2010 |
Publikationsreihe
| 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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
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SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 2010. S. 331-338 (SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › 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 -