An Approach to Modelling User Interests Using TF-IDF and Fuzzy Sets Qualitative Comparative Analysis - Artificial Intelligence Applications and Innovations (AIAI 2018) Access content directly
Conference Papers Year : 2018

An Approach to Modelling User Interests Using TF-IDF and Fuzzy Sets Qualitative Comparative Analysis

Abstract

Modelling and understanding user interests are particularly important tasks for designing services and building systems for customized solutions in web personalization and recommender systems. User generated content (UGC) constitutes a significant source of information for capturing user interests. This paper, suggests an approach to user profiling that analyses the Term Frequency (TF) and the Inverse Document Frequency (IDF) of selected tourism services by utilising the Fuzzy set Qualitative Comparative Analysis (FsQCA). It analyses a sample of customer reviews that are collected from tourism web sites. This paper considers the amount of money that customers spent during their hotel stay, as the outcome set in the FsQCA analysis. The results produce causal combinations of services that are necessary and sufficient for building customer interests models that best lead to the outcome and argue for the applicability of the FsQCA in modelling user interests.
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hal-01821054 , version 1 (22-06-2018)

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Dimitris K. Kardaras, Stavros Kaperonis, Stavroula Barbounaki, Ilias Petrounias, Kostas Bithas. An Approach to Modelling User Interests Using TF-IDF and Fuzzy Sets Qualitative Comparative Analysis. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.606-615, ⟨10.1007/978-3-319-92007-8_51⟩. ⟨hal-01821054⟩
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