Toward Mitigating Tourists' Indifference in POI Recommendation Systems Using MAS

EasyChair Preprint no. 11556

Abstract

POI recommendation is one of the artificial intelligence techniques used to personalize a user's experience in the field of smart tourism. However, this technique suffers from the problem of sparse data due to the indifference of the ratings of the places visited by the user. To mitigate this problem, we propose in this work a Multi-agent System for Reconciling POI Recommendation Algorithms (MSRPRA) using three types of POI recommendation algorithm that exploit user ratings, check-ins during visits and explicitly declared trust relationships between users. Additionally, a voting system is employed to merge the results of these three algorithms.

Keyphrases: collaboratif filtring, multiagent system, Point-of-Interest Recommendation

@Booklet{EasyChair:11556,
  author = {Zoulikha Maghni Sandid and Zohra Slama and Nassim Dennouni},
  title = {Toward Mitigating Tourists' Indifference in POI Recommendation Systems Using MAS},
  howpublished = {EasyChair Preprint no. 11556},

  year = {EasyChair, 2023}}