HAP-SAP:Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process

Dubey, Manisha and Srijith, P.K. and Desarkar, Maunendra Sankar (2020) HAP-SAP:Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process. In: GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 3 November 2020 - 6 November 2020.

Full text not available from this repository. (Request a copy)

Abstract

The prevalence of location-based social networks (LBSNs) has eased the understanding of human mobility patterns. However, categories which act as semantic characterization of the location, might be missing for some check-ins and can adversely affect modelling the mobility dynamics of users. At the same time, mobility patterns provide cues on the missing semantic categories. In this paper, we simultaneously address the problem of semantic annotation of locations and location adoption dynamics of users. We propose our model HAP-SAP, a latent spatio-temporal multivariate Hawkes process, which considers latent semantic category influences, and temporal and spatial mobility patterns of users. The inferred semantic categories can supplement our model on predicting the next check-in events by users. Our experiments on real datasets demonstrate the effectiveness of the proposed model for the semantic annotation and location adoption modelling tasks.

[error in script]

IITH Creators:

IITH Creators	ORCiD
Dubey, Manisha	UNSPECIFIED
Srijith, P K	UNSPECIFIED
Desarkar, Maunendra Sankar	UNSPECIFIED

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

Latent semantics; Location-based social networks; Mobility pattern; Semantic annotations; Semantic category; Semantic characterizations; Spatio temporal; Temporal and spatial

Subjects:

Computer science

Divisions:

Department of Computer Science & Engineering

Depositing User:

. LibTrainee 2021

Date Deposited:

10 Aug 2021 05:45

Last Modified:

09 Mar 2022 10:33

URI:

http://raiithold.iith.ac.in/id/eprint/8781