@conference {Enaanai2017,
	title = {The collaborative relevance in the distributed information retrieval},
	booktitle = {Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA},
	year = {2017},
	note = {cited By 0},
	abstract = {Relevance is one of the most interesting topics in the information retrieval domain. In this paper, we introduce another method of relevance calculation. We propose to use the implicit opinion of users to calculate relevance. The Implicit judgment of users is injected to the documents by calculating different kinds of weighting. These latter touch several criteria like as user{\textquoteright}s weight in the query{\textquoteright}s words, user{\textquoteright}s profile, user{\textquoteright}s interest, document{\textquoteright}s content and the document popularity. In this method, each user is an active element of the system, he searches documents and he makes treatments to provide relevant information to other users in the Network. This is similar as the peer-to-peer systems; unlike that, an element (user) have to manage automatically his data by creating a short view model of his most visited documents, and calculates his relative relevance about each one. The relative relevance is variable according each user, so the final relevance is calculated by the averaging of the elementary relevance of all users. Hence, the name of collaborative relevance. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/AICCSA.2016.7945827},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021875857\&doi=10.1109\%2fAICCSA.2016.7945827\&partnerID=40\&md5=24987a90a9345c06f11af61bc9d9e4c3},
	author = {Enaanai, A. and Doukkali, A.S. and Saif, I. and Moutachaouik, H. and Hain, M.}
}
@article {Saif2017210,
	title = {GENAUM: New semantic distributed search engine},
	journal = {Journal of Mobile Multimedia},
	volume = {13},
	number = {3-4},
	year = {2017},
	note = {cited By 0},
	pages = {210-221},
	abstract = {The rapid development of services based on distributed architectures is now emerging as important items that transform mode of communication, and the exponential growth of the Web makes a strong pressure on technologies, for a regular improvement of performance, so it{\textquoteright}s irresistible to use distributed architectures and techniques for the search and information retrieval on the Web, to provide more relevant search result, in minimum possible time. This paper discuss some solutions researchers are working on, to make search engines more faster and more intelligent, specifically by considering the semantic context of users and documents, and the use of distributed architectures. This paper also presents the overall architecture of GENAUM; the collaborative, semantic and distributed search engine, based on a network of agents, which is the core part of the system. The functionality of GENAUM is spread across multiple agents, to fulfill user{\textquoteright}s performance expectations. At the end of this paper, some preliminary experimental results are presented, that attempts to test the user modeling process of GENAUM, using reference ontology. {\textcopyright} Rinton Press.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040242169\&partnerID=40\&md5=21e9c1f654b188cfb9b0bcd523769494},
	author = {Saif, I. and Doukkali, A.S. and Enaanai, A. and Benlahmar, E.H.}
}
@article {Enaanai2012113,
	title = {Noise abatement in the Arabic IRS results by applying a sentences morphosemantic filter (gene filter method)},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {42},
	number = {1},
	year = {2012},
	note = {cited By 0},
	pages = {113-121},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867512204\&partnerID=40\&md5=2851a8dedc46b911edc6276bfd005dfe},
	author = {Enaanai, A. and Doukkali, A. and Regragui, B.}
}
