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- W2892636730 abstract "With the rapid development of location-based social networks (LBSNs), more and more people form the habit of sharing locations with their friends. Point of interest (POI) recommendation is aiming to recommend new places for users when they explore their surroundings. How to make proper recommendation has been a key point on the basis of existing information. In this paper, we propose a novel POI recommendation approach by fusing user preference, geographical influence and social reputation. TFIDF is used to represent user preference. Then, we further improve recommendation model by incorporating geographical distance and popularity. In the dataset, we find friends in LBSNs share low common visited POIs. Instead of directly getting recommendation from friends, users attain recommendation from others according to their reputation in the LBSNs. Finally, experimental results on real-world dataset demonstrate that the proposed method performs much better than other recommendation methods." @default.
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- W2892636730 date "2018-01-01" @default.
- W2892636730 modified "2023-10-08" @default.
- W2892636730 title "A Point of Interest Recommendation Approach by Fusing Geographical and Reputation Influence on Location Based Social Networks" @default.
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- W2892636730 doi "https://doi.org/10.1007/978-3-030-00916-8_22" @default.
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