Personalized Tourist Package Recommendation using Graph Based Approach

Hti, Rashmi and Desarkar, Maunendra Sankar (2018) Personalized Tourist Package Recommendation using Graph Based Approach. In: 26th Conference on User Modeling, Adaptation and Personalization, 08-11 July 2018, Singapore.

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Location Based Social Networks (LBSN) benefit the users by allowing them to share their locations and life moments with their friends. The users can also review the locations they have visited. Classical recommender systems provide users a ranked list of single items. This is not suitable for applications like trip planning,where the recommendations should contain multiple items in an appropriate sequence. The problem of generating such recommendations is challenging due to various critical aspects, which includes user interest, budget constraints and high sparsity in the available data used to solve the problem. In this paper, we propose a graph based approach to recommend a set of personalized travel packages. Each recommended package comprises of a sequence of multiple Point of Interests (POIs). Given the current location and spatio-temporal constraints, our goal is to recommend a package which satisfies the constraints. This approach utilizes the data collected from LBSNs to learn user preferences and also models the location popularity.

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IITH Creators:
IITH CreatorsORCiD
Desarkar, Maunendra SankarUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 17 Jul 2018 04:57
Last Modified: 17 Jul 2018 04:57
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