Predicting perceptual speed from search behaviour

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Abstract

Perceptual Speed (PS) is a cognitive ability that is known to affect multiple factors in Information Retrieval (IR) such as a user's search performance and subjective experience. However PS tests are difficult to administer which limits the design of user-adaptive systems that can automatically infer PS to appropriately accommodate low PS users. Consequently, this paper evaluated whether PS can be automatically classified from search behaviour using several machine learning models trained on features extracted from TREC Common Core search task logs. Our results are encouraging: given a user's interactions from one query, a Decision Tree was able to predict a user's PS as low or high with 86\% accuracy. Additionally, we identified different behavioural components for specific PS tests, implying that each PS test measures different aspects of a person's cognitive ability. These findings motivate further work for how best to design search systems that can adapt to individual differences.
Original languageEnglish
Title of host publicationSIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationNew York, NY.
Pages1989–1992
Number of pages4
DOIs
Publication statusPublished - 25 Jul 2020
EventThe 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020) - Xi'an, China
Duration: 25 Jul 202030 Jul 2020
Conference number: 43

Conference

ConferenceThe 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020)
Abbreviated titleSIGIR 2020
CountryChina
CityXi'an
Period25/07/2030/07/20

Keywords

  • perceptual speed
  • information retrieval
  • machine learning
  • search behaviour
  • information seeking

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    Datasets

    Data for: "Predicting Perceptual Speed from Search Behaviour"

    Foulds, O. (Creator), Suglia, A. (Contributor), Halvey, M. (Supervisor) & Azzopardi, L. (Supervisor), University of Strathclyde, 4 Jun 2020

    Dataset

    Cite this

    Foulds, O., Suglia, A., Azzopardi, L., & Halvey, M. (2020). Predicting perceptual speed from search behaviour. In SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1989–1992). https://doi.org/10.1145/3397271.3401210