@article {Mourchid2018,
	title = {CGAM: A community and geography aware mobility model},
	journal = {International Journal of Communication Systems},
	volume = {31},
	number = {1},
	year = {2018},
	doi = {10.1002/dac.3432},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030319469\&doi=10.1002\%2fdac.3432\&partnerID=40\&md5=9e90e1af7674bce27f60e78c6d502044},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@article {Mourchid2018,
	title = {CGAM: A community and geography aware mobility model},
	journal = {International Journal of Communication Systems},
	volume = {31},
	number = {1},
	year = {2018},
	note = {cited By 0},
	abstract = {The advances of localization-enabled technologies have led to huge volumes of large-scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context-aware advertising, city-wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio-temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members{\textquoteright} distribution, and radius of gyration. We validate the CGAM synthetic traces against real-world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding-based and community-based routing protocols. Copyright {\textcopyright} 2017 John Wiley \& Sons, Ltd.},
	doi = {10.1002/dac.3432},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030319469\&doi=10.1002\%2fdac.3432\&partnerID=40\&md5=9e90e1af7674bce27f60e78c6d502044},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@conference {Mourchid20171315,
	title = {A game-theoretic approach for non-overlapping communities detection},
	booktitle = {2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017},
	year = {2017},
	note = {cited By 1},
	pages = {1315-1320},
	abstract = {In this paper, we propose a game-theoretic approach to find the community structure in complex networks based on a non-cooperative game. This approach optimizes a node-based modularity for non-overlapping communities. Experiments show that our approach is effective to discover non-overlapping communities and obtain high values of modularity and Normalized Mutual Information (NMI) for real-world and synthetic networks in a reasonable time. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/IWCMC.2017.7986475},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027835444\&doi=10.1109\%2fIWCMC.2017.7986475\&partnerID=40\&md5=b0751b99b8a2552e780d327bef409ddf},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
@conference {Mourchid2017,
	title = {Random walk based co-occurrence prediction in location-based social networks},
	booktitle = {IEEE International Conference on Communications},
	year = {2017},
	note = {cited By 0},
	abstract = {In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental results demonstrate that our LBRW-Co model have substantial advantages over baseline approaches in predicting and ranking co-occurrence interactions. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/ICC.2017.7997209},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028326862\&doi=10.1109\%2fICC.2017.7997209\&partnerID=40\&md5=f865adbae7afd91e045cf307bb52ae7f},
	author = {Mourchid, F. and Kobbane, A. and Ben Othman, J. and El Koutbi, M.}
}
