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| Content Provider | ACM Digital Library |
|---|---|
| Author | Sydow, Marcin Bonchi, Francesco Donato, Debora Castillo, Carlos |
| Abstract | Topical query decomposition (TQD) is a paradigm recently introduced in [1], which, given a query, returns to the user a set of queries that cover the answer set of the original query. The TQD problem was studied as a variant of the set-cover problem and solved by means of a greedy algorithm. This paper aims to strengthen the original formulation by introducing a new global objective function, and thus formalising the problem as a combinatorial optimisation one. Such a reformulation defines a common framework allowing a formal evaluation and comparison of different approaches to TQD. We apply simulated annealing, a sub-optimal meta-heuristic, to the problem of topical query decomposition and we show, through a large experimentation on a data sample extracted from an actual query log, that such meta-heuristic achieves better results than the greedy algorithm. |
| Starting Page | 43 |
| Ending Page | 47 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781605584348 |
| DOI | 10.1145/1507509.1507516 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-02-09 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Query decomposition Query recommendation Query logs Simulated annealing Objective function |
| Content Type | Text |
| Resource Type | Article |
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