Predicting Search Task Difficulty through a Discrete‐Time Action Log Representation on Spectrum Kernel

Journal Article · 13 October 2022 · Proceedings of the Association for Information Science and Technology

DOI: https://doi.org/10.1002/pra2.692 · OSTI ID:1893194

Gacitúa, Daniel ^[1]; González‐Ibáñez, Roberto ^[1]

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1. Universidad de Santiago de Chile Chile

ABSTRACT Predicting perceived difficulty on a web search task is an open problem in the interactive information retrieval field. A common approach to tackle it, is through features obtained from full search sessions, which are then used to train classification models. In this poster we attempt to predict perceived task difficulty at different stages of the search process. To do so, we use the spectrum kernel for support vector machine (SVM) classification. Our preliminary results suggest that by using behavioral data from the first query segment, it is possible to provide timely classifications of whether a search task is perceived as hard or easy.

• Sponsoring Organization: USDOE
• OSTI ID: 1893194
• Journal Information: Proceedings of the Association for Information Science and Technology, Journal Name: Proceedings of the Association for Information Science and Technology Journal Issue: 1 Vol. 59; ISSN 2373-9231
• Publisher: Wiley Blackwell (John Wiley & Sons)Copyright Statement
• Country of Publication: Country unknown/Code not available
• Language: English