@conference {Mourchid2015213,
	title = {Mining user patterns for location prediction in mobile social networks},
	booktitle = {Colloquium in Information Science and Technology, CIST},
	volume = {2015-January},
	number = {January},
	year = {2015},
	note = {cited By 1},
	pages = {213-218},
	abstract = {Understanding human mobility dynamics is of an essential importance to today mobile applications, including context-aware advertising and city wide sensing applications. Recently, Location-based social networks (LBSNs) have attracted important researchers{\textquoteright} efforts, to investigate spatial, temporal and social aspects of user patterns. LBSNs allow users to {\textquoteright}check-in{\textquoteright} at geographical locations and share this information with friends. In this paper, analysis of check-ins data provided by Foursquare, the online location-based social network, allows us to construct a set of features that capture: spatial, temporal and similarity characteristics of user mobility. We apply this knowledge to location prediction problem, and combine these features in supervised learning for future location prediction. We find that the supervised classifier based on the combination of multiple features offers reasonable accuracy. {\textcopyright} 2014 IEEE.},
	doi = {10.1109/CIST.2014.7016621},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938084658\&doi=10.1109\%2fCIST.2014.7016621\&partnerID=40\&md5=86ede8ff82b4095f9bf55be3eaa192e2},
	author = {Mourchid, F.a and Habbani, A.a b and Koutbi, M.E.a}
}
@article {Lakki20151070,
	title = {Multi-objective dynamic metric and QoS in networks manets},
	journal = {Research Journal of Applied Sciences, Engineering and Technology},
	volume = {10},
	number = {9},
	year = {2015},
	note = {cited By 0},
	pages = {1070-1081},
	abstract = {The aim of this study is to find a Intelligent parameter which is based on mobility and Clustering. This metric will be integrate in the selection process of MPRs to improve QoS in Manets networks. The unpredictable mobility and the large quantity of generated traffic by each node interface make communication in network increasingly difficult to manage. Thus, routing protocols need to be adapted to such conditions. In order to make OLSR protocol more robust, piercing and more adaptable to the conditions dictated by the environment of each node, this study proposes a polymorphic metric that changes depending on the network behavior. This metric aims to make the OLSR protocol best suited to each zone. Many simulations would be undergone by NS2 to test and prove the validity of this new metric in environments with high mobility and quantity of traffic. {\textcopyright} Maxwell Scientific Organization, 2015.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940775201\&partnerID=40\&md5=be882576c747f7d2d3d54cd08dc7dc91},
	author = {Lakki, N.a and Ouacha, A.a and Habbani, A.a b and El Abbadi, J.a}
}
