A genetic‐based pairwise trip planner recommender system

Nunung Nurul Qomariyah; Dimitar Lubomirov Kazakov

doi:10.1186/s40537-021-00470-6

A genetic‐based pairwise trip planner recommender system

Nunung Nurul Qomariyah, Dimitar Lubomirov Kazakov

Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

The massive growth of internet users nowadays can be a big opportunity for the busi- nesses 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 prefer- ence 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.

Original language	English
Article number	77
Number of pages	23
Journal	Journal of Big Data
Volume	8
Issue number	77
DOIs	https://doi.org/10.1186/s40537-021-00470-6
Publication status	Published - 30 May 2021

Bibliographical note

Keywords

recommender systems
pairwise choice
genetic algorithm
preference learning

Access to Document

10.1186/s40537-021-00470-6

A genetic‑based pairwise trip planner recommender system
© The Author(s) 2021
Final published version, 3.36 MBLicence: CC BY

Cite this

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