Towards a personalized recommendation model in location-based social networks

Author First name, Last name, Institution

Reem Atassi, American University in the Emirates
Ons Al-Shamaileh, Zayed University
Hakim Hacid, Zayed University

Document Type

Conference Proceeding

Source of Publication

35th Annual European Simulation and Modelling Conference 2021, ESM 2021

Publication Date

1-1-2021

Abstract

We propose a hybrid recommendation model in Location-Based Social Networks (LBSN). The model is designed to recommend a list of Points of Interest (POIs), which is a tailored list of top-k venues, that meets user’s preferences. The model utilizes heterogeneous relations in location-based social networks to produce a high-quality recommendation and improve the user’s satisfaction on the recommended venues. The proposed model utilizes Meta Path-Based Search, to estimate the similarity between the user and the venues located within the area of interest.

ISBN

9789492859181

First Page

216

Last Page

223

Disciplines

Computer Sciences

Keywords

Hybrid recommendation, Location-based social networks, Meta path-based search, Recommendation system

Scopus ID

85119619893

Recommended Citation

Atassi, Reem; Al-Shamaileh, Ons; and Hacid, Hakim, "Towards a personalized recommendation model in location-based social networks" (2021). All Works. 4703.
https://zuscholars.zu.ac.ae/works/4703

Indexed in Scopus

yes

Open Access

no