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A Comparative Analysis of Human and Automatic Query Variants

conference contribution
posted on 2024-11-03, 12:39 authored by Binsheng Liu, Nick Craswell, Xiaolu Lu, Oren Kurland, Shane CulpepperShane Culpepper
We present an in-depth comparative analysis of the effectiveness distributions of sets of human-created and automatically-created query variations used to represent the same information need. The automatic variations are generated using Bing's click graph. Experiments performed with TREC datasets show that using automatic variations for retrieval can result in similar effectiveness to that of using human variations, although the two types of variations can be appreciably different in several important respects --- e.g., their similarities and corresponding retrieved lists.

Funding

Trajectory data processing: Spatial computing meets information retrieval

Australian Research Council

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New approaches to interactive sessional search for complex tasks

Australian Research Council

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History

Related Materials

  1. 1.
    DOI - Is published in 10.1145/3341981.3344223
  2. 2.
    ISBN - Is published in 9781450368810 (urn:isbn:9781450368810)

Start page

47

End page

50

Total pages

4

Outlet

Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR 2019)

Name of conference

ICTIR 2019

Publisher

ACM

Place published

New York, United States

Start date

2019-10-02

End date

2019-10-05

Language

English

Copyright

© 2019 Copyright held by the owner/author(s).

Former Identifier

2006095052

Esploro creation date

2020-06-22

Fedora creation date

2019-12-02

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