Open Access

ARTICLE

Accurate Location Prediction of Social‐Users Using mHMM

Ahsan Hussain, Bettahally N. Keshavamurthy, Ravi Prasad K. Jagannath

National Institute of Technology Goa, Ponda, Goa, 403401, India.

* Corresponding Author: Ahsan Hussain,

Intelligent Automation & Soft Computing 2019, 25(3), 473-486. https://doi.org/10.31209/2018.11007092

Abstract

Prediction space of distinct check-in locations in Location-Based Social Networks is a challenge. In this paper, a thorough analysis of Foursquare Check-ins is done. Based on previous check-in sequences, next location of social-users is accurately predicted using multinomial-Hidden Markov Model (mHMM) with Steady-State probabilities. This information benefits security-agencies in tracking suspects and restaurant-owners to predict their customers’ arrivals at different venues on given days. Higher accuracy and Steady-State venuepopularities obtained for location-prediction using the proposed method, outperform various other baseline methods.

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Keywords

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