GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations

By Jia-Dong Zhang, Chi-Yin Chow. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

319 citations recorded by the source corpus.

Subfields: Information Systems, Sociology and Political Science, Transportation

View Paper: https://www.semanticscholar.org/paper/5d2f74196db4eda230828a061b75acfe0a127031

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Carl Yang
2. Quan Yuan
3. Jiawei Han
4. Chao Zhang
5. Lanxiao Bai
6. Cynthia Rudin
7. Xifeng Yan
8. George Karypis

In Sociology and Political Science

1. Quan Yuan
2. Jiawei Han

In Transportation

1. Quan Yuan
2. Jiawei Han

Citations in the corpus

• Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation (2017, background): “While traditional recommender systems mostly work with ratings and reviews [20], POI recommendations naturally come with various context, such as geographical information [24, 25, 28, 47, 49], categorical information [53, 55], social information [22, 38, 50, 52], temporal information [48, 56], etc.”