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Khalil M El Hindi

Professor

Faculty memeber

علوم الحاسب والمعلومات
Room 2189, Building 31
publication
Journal Article
2020

Venue-Popularity Prediction Using Social Data Participatory Sensing Systems and RNNs

Khulud-Alharthy, Khalil El Hindi Salaha Alzahrani . 2020

Analyzing social data as a participatory sensing system (PSS) provides a deep understanding of city dynamics, such as people’s mobility patterns, social patterns, and events detection. In a PSS, individuals with mobile devices sense their environment, collect, and share data. For smart cities, intelligent city dynamics analysis has many applications such as for urban planning, transportation systems, city environment, energy consumption, public safety, and city economy. This study aimed to develop an intelligent application to predict the potential number of visitors for specific venues based on the analysis of mobility patterns of individuals. The ability to accurately predict the number of visitors to a venue allows authorities to better understand the behavior of the people and allocate recourses accordingly. We formulated the venue-popularity problem as a sequence-based regression and classification problem. We employed three recurrent neural network (RNN)-based models to predict the locations of popular venues on a city map. The proposed models include basic RNN, long short-term memory (LSTM), and gated recurrent unit (GRU). We constructed several social datasets for Riyadh city using Twitter and Foursquare as the PSS. Our results revealed that modeling venue-popularity prediction as a sequence regression problem yields better results than modeling it as a sequence classification problem. For the city-popularity map prediction problem, the vector autoregression baseline model achieved better performance than the RNN-family models.

Volume Number
9
Magazine \ Newspaper
IEEE Access
Pages
3140 - 3154
more of publication
publications

The combination of collaborative deep learning and Cyber-Physical Systems (CPSs) has the potential to improve decision-making, adaptability, and efficiency in dynamic and distributed environments…

by Alya Alshammari, and Khalil El Hindi
Published in:
Applied Sciences
publications

Naïve Bayes (NB) classification performance degrades if the conditional independence assumption is not satisfied or if the conditional probability estimate is not realistic due to the attributes…

by Fahad S. Alenazi, Khalil El Hindi, and Basil AsSadhan