Probabilistic identification of visited point-of-interest for personalized automatic check-in

Author:

Nishida Kyosuke1,Toda Hiroyuki2,Kurashima Takeshi2,Suhara Yoshihiko2

Affiliation:

1. NTT Resonant Inc. Minato, Tokyo, Japan

2. NTT Service Evolution Laboratories, NTT Corporation Yokosuka, Kanagawa, Japan

Publisher

ACM

Reference48 articles.

1. Extraction of social context and application to personal multimedia exploration

2. Android Developers. Location. http://developer.android.com/reference/android/location/Location.html {Online}. Android Developers. Location. http://developer.android.com/reference/android/location/Location.html {Online}.

3. Using GPS to learn significant locations and predict movement across multiple users

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2. Aggregate Learning for Mixed Frequency Data;2022 IEEE International Conference on Big Data (Big Data);2022-12-17

3. Understanding Location Privacy of the Point-of-Interest Aggregate Data via Practical Attacks and Defenses;IEEE Transactions on Dependable and Secure Computing;2022

4. Practical Location Privacy Attacks and Defense on Point-of-interest Aggregates;2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS);2021-07

5. Spatio-Temporal Dual Graph Attention Network for Query-POI Matching;Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval;2020-07-25

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