Query Performance Prediction Focused on Summarized Letor Features-Reference-Cited by-同舟云学术

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Query Performance Prediction Focused on Summarized Letor Features

Published:2018-06-27 Issue: Volume: Page:
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Container-title:The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
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Author:

Chifu Adrian-Gabriel¹,Laporte Léa²,Mothe Josiane³,Ullah Md Zia⁴

Affiliation:

1. Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France

2. INSA Lyon, LIRIS, UMR 5205 CNRS, Lyon, France

3. ESPE, Université de Toulouse, IRIT, UMR5505 CNRS, Toulouse, France

4. UPS, Université de Toulouse, IRIT, UMR5505 CNRS, Toulouse, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3209978.3210121

Reference22 articles.

1. G. Amati C. Carpineto and G. Romano . 2004. Query difficulty robustness and selective application of query expansion ECIR. 127--137. G. Amati C. Carpineto and G. Romano . 2004. Query difficulty robustness and selective application of query expansion ECIR. 127--137.

2. Niranjan Balasubramanian and James Allan . 2010. Learning to select rankers. In ACM SIGIR. 855--856. 10.1145/1835449.1835650 Niranjan Balasubramanian and James Allan . 2010. Learning to select rankers. In ACM SIGIR. 855--856. 10.1145/1835449.1835650

3. Combining pre-retrieval query quality predictors using genetic programming

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