A genetic-based pairwise trip planner recommender system

Qomariyah N.N., Kazakov D.

Computer Science Department, Faculty of Computing and Media, Bina Nusantara University, Jakarta, 11480, Indonesia; Computer Science Department, University of York, York, United Kingdom


Abstract

The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study. © 2021, The Author(s).

Genetic algorithm; Pairwise preferences; Preference learning; Recommender system


Journal

Journal of Big Data

Publisher: Springer Science and Business Media Deutschland GmbH

Volume 8, Issue 1, Art No 77, Page – , Page Count


Journal Link: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107034783&doi=10.1186%2fs40537-021-00470-6&partnerID=40&md5=582944eec452e06bba2c921768cf8979

doi: 10.1186/s40537-021-00470-6

Issn: 21961115

Type: All Open Access, Gold, Green


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