What makes a query temporally sensitive?

Craig Willis, Garrick Sherman, Miles James Efron

Research output: Contribution to journalArticlepeer-review

Abstract

This work examines factors that affect manual classifications of “temporally sensitive” information needs. We introduce the concepts of temporal relevance and temporal topicality to differentiate between different aspects of temporal retrieval research. We use qualitative and quantitative techniques to analyze 660 topics from the Text Retrieval Conference (TREC) previously used in the experimental evaluation of temporal retrieval models. We use regression analysis to model previous manual classifications. We identify factors and potential problems with previous classifications, proposing principles and guidelines for future work on the evaluation of temporal retrieval models.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalProceedings of the Association for Information Science and Technology
Volume53
Issue number1
DOIs
StatePublished - Jan 1 2016

ASJC Scopus subject areas

  • Computer Science(all)
  • Library and Information Sciences

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