Learning by Example: training users through high-quality query suggestions

Morgan Harvey, Claudia Hauff, David Elsweiler

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

The queries submitted by users to search engines often poorly describe their information needs and represent a potential bottleneck in the system. In this paper we investigate to what extent it is possible to aid users in learning how to formulate better queries by providing examples of high-quality queries interactively during a number of search sessions. By means of several controlled user studies we collect quantitative and qualitative evidence that shows: (1) study participants are able to identify and abstract qualities of queries that make them highly effective, (2) after seeing high-quality example queries participants are able to themselves create queries that are highly effective, and, (3) those queries look similar to expert queries as defined in the literature. We conclude by discussing what the findings mean in the context of the design of interactive search systems.
Original languageEnglish
Title of host publicationSIGIR '15: 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages133-142
Number of pages10
DOIs
Publication statusPublished - 2015

Fingerprint Dive into the research topics of 'Learning by Example: training users through high-quality query suggestions'. Together they form a unique fingerprint.

  • Cite this

    Harvey, M., Hauff, C., & Elsweiler, D. (2015). Learning by Example: training users through high-quality query suggestions. In SIGIR '15: 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 133-142) https://doi.org/10.1145/2766462.2767731