User Perspectives on Query Difficulty

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  • ictir2011

    Submitted manuscript, 407 KB, PDF document

The difficulty of a user query can affect the performance of Information Retrieval (IR) systems. What makes a query difficult and how one may predict this is an active research area, focusing mainly on factors relating to the retrieval algorithm, to the properties of the retrieval data, or to statistical and linguistic features of the queries that may render them difficult. This work addresses query difficulty from a different angle, namely the users’ own perspectives on query difficulty. Two research questions are asked: (1) Are users aware that the query they submit to an IR system may be difficult for the system to address? (2) Are users aware of specific features in their query (e.g., domain-specificity, vagueness) that may render their query difficult for an IR system to address? A study of 420 queries from a Web search engine query log that are pre-categorised as easy, medium, hard by TREC based on system performance, reveals an interesting finding: users do not seem to reliably assess which query might be difficult; however, their assessments of which query features might render queries difficult are notably more accurate. Following this, a formal approach is presented for synthesising the user-assessed causes of query difficulty through opinion fusion into an overall assessment of query difficulty. The resulting assessments of query difficulty are found to agree notably more to the TREC categories than the direct user assessments.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval Theory : Lecture Notes in Computer Science, 2011, Volume 6931/2011, 3-14, DOI: 10.1007/978-3-642-23318-0_3
Publication date2011
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference on the Theory of Information Retrieval - Bertinoro, Italy
Duration: 12 Sep 201114 Sep 2011


ConferenceInternational Conference on the Theory of Information Retrieval
SeriesLecture notes in computer science

Bibliographical note

G. Amati and F. Crestani (Eds.): ICTIR 2011, LNCS 6931, pp. 3–14, 2011.
c Springer-Verlag Berlin Heidelberg 2011

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