Cited By
View all- Islam MAsadi MAmer-Yahia SRoy S(2022)A generic framework for efficient computation of top-k diverse resultsThe VLDB Journal10.1007/s00778-022-00770-032:4(737-761)Online publication date: 28-Nov-2022
Beyond Greedy Search: Pruned Exhaustive Search for Diversified Result Ranking
Pages 99 - 106
Abstract
As a search query can correspond to multiple intents, search result diversification aims at returning a single result list that could satisfy as many users' information needs as possible. However, determining the optimal ranking list is NP-hard. Several algorithms have been proposed to obtain a local optimal ranking with greedy approximations. In this paper, we propose a pruned exhaustive method to generate better solutions than the greedy search. Our approach is based on the observations that there are fewer than ten subtopics for most queries, most relevant results cover only a few subtopics, and most search users only focus on the top results. The proposed pruned exhaustive search algorithm based on ordered pairs (PesOP) finds the optimal solution efficiently. Experimental results based on TREC Diversity and NTCIR Intent task datasets show that PesOP outperforms greedy strategies with better diversification performance. Compared with the original non-pruned exhaustive search, the PesOP algorithm decreases the computational cost while maintaining optimality.
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Index Terms
- Beyond Greedy Search: Pruned Exhaustive Search for Diversified Result Ranking
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Information & Contributors
Information
Published In
September 2018
238 pages
ISBN:9781450356565
DOI:10.1145/3234944
- General Chairs:
- Dawei Song,
- Tie-Yan Liu,
- Le Sun,
- Program Chairs:
- Peter Bruza,
- Massimo Melucci,
- Fabrizio Sebastiani,
- Grace Hui Yang
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Publication History
Published: 10 September 2018
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- Research-article
Funding Sources
- National Key Basic Research Program
- Natural Science Foundation of China
- NIH
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ICTIR '18
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ICTIR '18: The 2018 ACM SIGIR International Conference on the Theory of Information Retrieval
September 14 - 17, 2018
Tianjin, China
Acceptance Rates
ICTIR '18 Paper Acceptance Rate 19 of 47 submissions, 40%;
Overall Acceptance Rate 235 of 527 submissions, 45%
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Cited By
View all- Islam MAsadi MAmer-Yahia SRoy S(2022)A generic framework for efficient computation of top-k diverse resultsThe VLDB Journal10.1007/s00778-022-00770-032:4(737-761)Online publication date: 28-Nov-2022
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