DivQ: diversification for keyword search over structured databases

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 nDCG-W and WS-recall, an adaptation of -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. Categories and Subje...

• Type: Journal
• Year: 2010
• Where: SIGIR
• Authors: Elena Demidova, Peter Fankhauser, Xuan Zhou, Wolfgang Nejdl
• Keywords: Information Technology, Interpretations, Keyword Query, SIGIR 2010, Structured