A Multi-objective Framework for Location Recommendation Based on User Preference

Location recommendation has attracted increasing attention in recent years. This paper proposes a novel multi-objective framework for location recommendation based on user preference. Under this framework, user preference can be separated into common preference and individual preference. Then two co...

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Bibliographic Details
Published in2017 13th International Conference on Computational Intelligence and Security (CIS) pp. 39 - 43
Main Authors Wang, Shanfeng, Gong, Maoguo, Qin, Can, Yang, Junwei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2017
Subjects
Algorithm design and analysis
Biological cells
Computational modeling
Evolutionary computation
Kernel
Linear programming
Location recommendation
Multi-objective evolutionary algorithm
Prediction algorithms
User preference
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Summary:Location recommendation has attracted increasing attention in recent years. This paper proposes a novel multi-objective framework for location recommendation based on user preference. Under this framework, user preference can be separated into common preference and individual preference. Then two contradictory objective functions are designed to describe these two kinds of preferences. It is difficult to optimize these two objective functions simultaneously. In this paper, a novel multi-objective evolutionary algorithm is proposed to optimize these two objective functions. The proposed algorithm can make a good balance between these two objective functions. Experiments on two real application recommendation scenarios: Foursquare dataset and Gowalla dataset show that the proposed algorithm is effective to recommend locations.
DOI:10.1109/CIS.2017.00017