Home // HUSO 2018, The Fourth International Conference on Human and Social Analytics // View article
Authors:
Dimitris Kardaras
Ilias Petrounias
Stavroula Barbounaki
Stavros Kaperonis
Keywords: Web Adaptation; TF-IDF; AHP; Multi-Criteria Analysis
Abstract:
User reviews provide a rich source of information regarding user interests. Many Web platforms allow or even encourage their visitors to leave their feedback regarding the products and services they have consumed. The Term Frequency (TF) and the Inverse Document Frequency (IDF) are two factors that have been used extensively in capturing users’ preferences. This paper collects users’ reviews from e-tourism Web platforms, calculates the TF and the IDF for each user and adopts a multi-criteria approach in order to quantify users’ preferences and dynamically adapt the websites design accordingly. It utilizes the Analytic Hierarchy Process (AHP) and similarity methods in order to determine the relative importance of terms and Web pages and then rearranges them in a new website structure.
Pages: 60 to 65
Copyright: Copyright (c) IARIA, 2018
Publication date: June 24, 2018
Published in: conference
ISSN: 2519-8351
ISBN: 978-1-61208-648-4
Location: Venice, Italy
Dates: from June 24, 2018 to June 28, 2018