Eldawy, E. E. O., A. Hendawi, M. Abdalla, and H. M. O. Mokhtar, "FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection", isprs International Journal of Geo-Information, vol. 10, issue 11, pp. 1-22, 2021.
Eldawy, E. E. O., A. Hendawi, M. Abdalla, and H. M. O. Mokhtar, "FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection", isprs International Journal of Geo-Information, vol. 10, issue 11, pp. 1-22, 2021.
Eldawy, E. E. O., A. Hendawi, M. Abdalla, and H. M. O. Mokhtar, "FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection", isprs International Journal of Geo-Information, vol. 10, issue 11, pp. 1-22, 2021.
Eldawy, E. E. O., A. Hendawi, M. Abdalla, and H. M. O. Mokhtar, "FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection", isprs International Journal of Geo-Information, vol. 10, issue 11, pp. 1-22, 2021.
Abdalla, M., H. M. O. Mokhtar, and N. ElGamal, "HarmonyMoves: A Unified Prediction Approach for Moving Object Future Path", (IJACSA) International Journal of Advanced Computer Science and Applications, vol. 11, issue 1, pp. 637-644, 2020.
Wageeh, H., H. Mokhtar, and S. Ghoniemy, "Exploring Trusted Relations among Virtual Interactions in Social Networks for Detecting Influence Diffusion", ISPRS Int. J. Geo-Information , vol. 8, issue 9, pp. 415, 2019/09/16. Abstract

n/a

Mohamed, D., A. El-Kilany, and H. M. O. Mokhtar, "Academic Articles Recommendation Using Concept- Based Representation", Intelligent Systems Conference (IntelliSys), 3-4 September, 2020.
Wagih, H. M., and H. M. O. Mokhtar, "Ridology: An Ontology Model for Exploring Human Behavior Trajectories in Ridesharing Applications", Recent Advances in Intelligent Systems and Smart Applications, Cham, Springer International Publishing, pp. 553–567, 2020. Abstract

The increasing adoption of social network applications has been an important source of information nowadays. The analysis of human behaviors in social networks has been brought to the forefront of several studies. Location-Based Social Networks (LBSN) are one of the possible means that allow the prediction of human behaviors through the efficient analysis of user's mobility patterns. Despite the remarkable progress in this research direction, however, LBSN is still hindered by the lack of literature defining the semantic aspects of the user's mobility. This research presents a contribution to the latest knowledge representation languages and Semantic Web technologies. We focus on studying human behavior mobility which is the core in location recommendation systems. Bringing to the ridesharing context, an ontology model with its underlying description logics to efficiently annotate human mobility is presented. Finally, experimental results, performed on two location-based social networks, namely, Brightkite (https://snap.stanford.edu/data), and BlaBlaCar (https://www.blablacar.co.uk/) are presented.

Habib, W., H. Mokhtar, and M. E. El-Sharkawi, "Weight-Based K-Truss Community Search via Edge Attachment", IEEE Access, vol. 8, pp. 148841 - 148852, 08, 2020. Abstract

n/a

Saddad, E., A. El-Bastawissy, H. M. O. Mokhtar, and M. Hazman, "Lake Data Warehouse Architecture for Big Data Solutions", International Journal of Advanced Computer Science and Applications, vol. 11, 01, 2020. Abstract

n/a

Tourism