Exploiting collective knowledge with three-way decision theory: Cases from the questionnaire-based research

Federico Cabitza, Davide Ciucci, Angela Locoro

Research output: Contribution to journalArticle

Abstract

Two methods are proposed for collective knowledge extraction from questionnaires with ordinal scales and dichotomous questions. Both methods are based on a three-way decision procedure and a statistical method aimed at attaining statistical significance of the above decision. One method is aimed at giving an (absolute) assessment of “objects” according to a given “criterion” and the other one at producing a relative ranking of the “objects”. A criterion can be related to one or more questionnaire items (usually questions or statements). In this latter case a method to compose ordinal items in aggregate scores is also given. The paper also presents two various case studies that illustrate the methods and give motivations for their application in different domains where the knowledge of a community or any distributed group of experts can be externalized (in terms of users' perceptions, attitudes, opinions, choices) with a structured closed-ended questionnaire.

Original languageEnglish
Pages (from-to)356-370
Number of pages15
JournalInternational Journal of Approximate Reasoning
Volume83
DOIs
Publication statusPublished - Apr 1 2017

Keywords

  • Collective knowledge
  • Online questionnaires
  • Three-way decision
  • User study

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

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