A faceted approach to conceptualizing tasks in information seeking

  • Authors:

  • Yuelin Li;Nicholas J. Belkin

  • Affiliations:

  • School of Library and Information Science, The University of Southern Mississippi, 118 College Drive #5146, Hattiesburg, MS 39401, United States;School of Communication, Information and Library Studies, Rutgers University, 4 Huntington Street, New Brunswick, NJ 08901, United States

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2008

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Abstract

The nature of the task that leads a person to engage in information interaction, as well as of information seeking and searching tasks, have been shown to influence individuals' information behavior. Classifying tasks in a domain has been viewed as a departure point of studies on the relationship between tasks and human information behavior. However, previous task classification schemes either classify tasks with respect to the requirements of specific studies or merely classify a certain category of task. Such approaches do not lead to a holistic picture of task since a task involves different aspects. Therefore, the present study aims to develop a faceted classification of task, which can incorporate work tasks and information search tasks into the same classification scheme and characterize tasks in such a way as to help people make predictions of information behavior. For this purpose, previous task classification schemes and their underlying facets are reviewed and discussed. Analysis identifies essential facets and categorizes them into Generic facets of task and Common attributes of task. Generic facets of task include Source of task, Task doer, Time, Action, Product, and Goal. Common attributes of task includes Task characteristics and User's perception of task. Corresponding sub-facets and values are identified as well. In this fashion, a faceted classification of task is established which could be used to describe users' work tasks and information search tasks. This faceted classification provides a framework to further explore the relationships among work tasks, search tasks, and interactive information retrieval and advance adaptive IR systems design.