Abstract
We explore how to generate effective queries based on search tasks. Our approach has three main steps: 1) identify search tasks based on research goals, 2) manually classify search queries according to those tasks, and 3) compare three methods to improve search rankings based on the task context. The most promising approach is based on expanding the user's query terms using task terms, which slightly improved the NDCG@20 scores over a BM25 baseline. Further improvements might be gained if we can identify more specific search tasks.
Original language | English |
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Publisher | arXiv |
Pages | 1-16 |
DOIs | |
Publication status | Published - 23 Oct 2020 |
Bibliographical note
Update version 2: Improved title Update version 3: corrected terminology hyponym -> hypernym in two instances Documents our participation to the TREC-COVID track. Contains 16 pages, 0 figuresKeywords
- cs.IR