How Effective are Proximity Scores in Term Dependency Models?-Reference-Cited by-同舟云学术

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How Effective are Proximity Scores in Term Dependency Models?

Published:2014 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2014 Australasian Document Computing Symposium on - ADCS '14
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Author:

Lu Xiaolu,Moffat Alistair,Culpepper J. Shane

Funder

Australian Research Council

Publisher

ACM Press

Reference19 articles.

1. M. Bendersky and W. B. Croft. Modeling higher-order term dependencies in information retrieval using query hypergraphs. In Proc. SIGIR, pages 941--950, 2012.

2. M. Bendersky, D. Metzler, and W. B. Croft. Parameterized concept weighting in verbose queries. In Proc. SIGIR, pages 605--614, 2011.

3. A. Broschart and R. Schenkel. High-performance processing of text queries with tunable pruned term and term pair indexes. ACM Trans. Information Systems, 30(1):1--32, 2012.

4. S. Büttcher, C. L. A. Clarke, and B. Lushman. Term proximity scoring for ad-hoc retrieval on very large text collections. In Proc. SIGIR, pages 621--622, 2006.

5. I. Cetindil, J. Esmaelnezhad, T. Kim, and C. Li. Efficient instant-fuzzy search with proximity ranking. In Proc. ICDE, pages 328--339, 2014.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Risk-Reward Trade-offs in Rank Fusion;Proceedings of the 22nd Australasian Document Computing Symposium;2017-12-07

2. Improving Search using Proximity-Based Statistics;Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval;2015-08-09

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