@Article{2018.11007092,
AUTHOR = {Ahsan Hussain, Bettahally N. Keshavamurthy, Ravi Prasad K. Jagannath},
TITLE = {Accurate Location Prediction of Social‐Users Using mHMM},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {3},
PAGES = {473--486},
URL = {http://www.techscience.com/iasc/v25n3/39671},
ISSN = {2326-005X},
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.},
DOI = {10.31209/2018.11007092}
}