TY - EJOU AU - Hussain, Ahsan AU - Keshavamurthy, Bettahally N. AU - Jagannath, Ravi Prasad K. TI - Accurate Location Prediction of Social‐Users Using mHMM T2 - Intelligent Automation \& Soft Computing PY - 2019 VL - 25 IS - 3 SN - 2326-005X AB - 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. KW - Foursquare Check-ins KW - Hidden Markov Model KW - Location-Based Social Networks KW - Location Prediction KW - Temporal Context DO - 10.31209/2018.11007092