Linked Open Data in Location-Based Recommendation System on Tourism Domain: a Survey

50Citations
Citations of this article
112Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Linked open data is a relatively new topic area with great potential in a wide range of fields. In the tourism domain, many studies are using linked open data to address the problem of location-based recommendation by integrating data with other linked open datasets to enrich data and tourism content for reacting to the needs of tourists. This work aims not only to present a systematic review and mapping of the linked open data in location-based recommendation system on tourism domain, but also to provide an overview of the current research status in the area. First, we classify journal papers in this area from 2001 to 2018 by the year of publication. Second, we analyze and categorize journal papers by the different recommendation applications including problem formulations, data collections, proposed algorithms/systems, and experimental results. Third, we group the linked open data sources used in location-based recommendation system on tourism. Next, we summarize the research achievements and present the distribution of the different categories of location-based recommendation applications via linked open data. Last, we also guide the possible future research direction for the linked open data in location-based recommendations on tourism.

Cite

CITATION STYLE

APA

Yochum, P., Chang, L., Gu, T., & Zhu, M. (2020). Linked Open Data in Location-Based Recommendation System on Tourism Domain: a Survey. IEEE Access, 8, 16409–16439. https://doi.org/10.1109/aCCESS.2020.2967120

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free