Modeling Implicit Communities from Geo-tagged Event Traces using Spatio-Temporal Point Processes

Ankita Likhyani, Vinayak Gupta, Srijith PK, Deepak Padmanabhan, Srikanta Bedathur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The location check-ins of users through various location-based services such as Foursquare, Twitter, and Facebook Places, etc., generate large traces of geo-tagged events. These event-traces often manifest in hidden (possibly overlapping) communities of users with similar interests. Inferring these implicit communities is crucial for forming user profiles for improvements in recommendation and prediction tasks. Given only time-stamped geo-tagged traces of users, can we find out these implicit communities, and characteristics of the underlying influence network? Can we use this network to improve the next location prediction task?
In this paper, we focus on the problem of community detection as well as capturing the underlying diffusion process and propose a model CoLAB based on Spatio-temporal point processes in continuous time but discrete space of locations that simultaneously models the implicit communities of users based on their check-in activities, without making use of their social network connections. CoLAB captures the semantic features of the location, user-to-user influence along with spatial and temporal preferences of users. To learn the latent community of users and model parameters, we propose an algorithm based on stochastic variational inference. To the best of our knowledge, this is the first attempt at jointly modeling the diffusion process with activity-driven implicit communities. We demonstrate CoLAB achieves up to 27% improvements in location prediction task over recent deep point-process based methods on geo-tagged event traces collected from Foursquare check-ins.
Original languageEnglish
Title of host publication21st International Conference on Web Information Systems Engineering (WISE 2020)
Subtitle of host publicationWISE 2020
Publication statusAccepted - 23 Jul 2020
Event21th International Conference on Web Information Systems Engineering: WISE 2020 -
Duration: 20 Oct 202024 Oct 2020
http://wasp.cs.vu.nl/WISE2020/

Conference

Conference21th International Conference on Web Information Systems Engineering
Period20/10/202024/10/2020
Internet address

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