Point-of-Interest Recommendation Based on Link Prediction in Bipartite Network

Yıl 2021, Cilt: IDAP-2021 : 5th International Artificial Intelligence and Data Processing symposium Sayı: Special, 154 - 161, 20.10.2021

Elifgül Çakmak Buket Kaya , Mehmet Kaya

https://doi.org/10.53070/bbd.990742

Öz

The use of location-based social networks is increasing day by day. In these networks, users check-in Point of Interest (POI) that they like, and in a sense, they advise future users. The aim of this paper is to detect whether users from the same hometown check-in for similar POIs using the link prediction method, thus recommending new POIs. The method first models the user-POI bipartite network, and then new recommendations are generated by the link prediction method. Experiments conducted on real data in Foursquare have shown that the proposed method achieves high accuracy values.

Anahtar Kelimeler

Machine Learning, Recommendation Systems, Location Based Social Networks, Point of Interest

İki Parçalı Ağda Bağlantı Tahminine Dayalı İlgi Çekici Nokta Tavsiyesi

Öz

Konum tabanlı sosyal ağların kullanımı her geçen gün artmaktadır. Bu ağlarda kullanıcılar beğendikleri ilgi noktalarını (POI) check-in yapar ve bir anlamda gelecekteki kullanıcılara tavsiyelerde bulunurlar. Bu makalenin amacı, bağlantı tahmini yöntemini kullanarak aynı memleketteki kullanıcıların benzer POI'ler için check-in yapıp yapmadıklarını tespit etmek ve böylece yeni POI'ler önermektir. Yöntem önce kullanıcı-POI ikili ağını modeller ve ardından bağlantı tahmin yöntemi tarafından yeni öneriler oluşturulur. Foursquare'de gerçek veriler üzerinde yapılan testler, önerilen yöntemin yüksek doğruluk değerlerine ulaştığını göstermiştir.

Anahtar Kelimeler

Makine Öğrenmesi, Tavsiye Sistemler, Konum Tabanlı Sosyal Ağlar, İlgi Çekici Nokta

Kaynakça

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