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- W2153193797 abstract "Query-by-example information retrieval provides users a flexible but efficient way to accurately describe their information needs. The query exemplars are usually long and in the form of either a partial or even a full document. However, they may contain extraneous terms that would have potential negative impacts on the retrieval performance. In order to alleviate those negative impacts, we propose a novel term-based query reduction mechanism so as to improve the informativeness of verbose query exemplars. We also explore the notion of term discrimination power to select a salient subset of query terms automatically. Experiments on the TDT Chinese collection show that the proposed approach is indeed effective and promising." @default.
- W2153193797 created "2016-06-24" @default.
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- W2153193797 date "2011-05-01" @default.
- W2153193797 modified "2023-10-16" @default.
- W2153193797 title "Handling verbose queries for spoken document retrieval" @default.
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- W2153193797 doi "https://doi.org/10.1109/icassp.2011.5947617" @default.
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