@conference { ISI:000373736100043,
	title = {Building rich user profile based on intentional perspective},
	booktitle = {INTERNATIONAL CONFERENCE ON ADVANCED WIRELESS INFORMATION AND COMMUNICATION TECHNOLOGIES (AWICT 2015)},
	series = {Procedia Computer Science},
	volume = {73},
	year = {2015},
	note = {International Conference on Advanced Wireless Information and Communication Technologies (AWICT), Natl Sch Engineers Sousse, TUNISIA, OCT 05-07, 2015},
	pages = {342-349},
	abstract = {Internet technologies evolution, from Web 1.0 to web 2.0 and web 3.0, has led us towards the definition of new requirements to be considered in the design and development of new application. It is important to note that depending solely on the request to satisfy user need is not effective. Indeed, the emergence of many researches related to the study of user behaviour has enhanced the retrieval information effectiveness. Typically, the context and the user profile are the main elements to characterize the user. Hence, we aim through this contribution to build a rich profile and to provide him suitable services. (C) 2015 The Authors. Published by Elsevier B.V.},
	issn = {1877-0509},
	doi = {10.1016/j.procs.2015.12.002},
	author = {Alaoui, Sara and El Idrissi, Younes El Bouzekri and Ajhoun, Rachida},
	editor = {Boubiche, DE and Hidoussi, F and Cruz, HT}
}
@conference { ISI:000373736100013,
	title = {The context in automatic spell correction},
	booktitle = {INTERNATIONAL CONFERENCE ON ADVANCED WIRELESS INFORMATION AND COMMUNICATION TECHNOLOGIES (AWICT 2015)},
	series = {Procedia Computer Science},
	volume = {73},
	year = {2015},
	note = {International Conference on Advanced Wireless Information and Communication Technologies (AWICT), Natl Sch Engineers Sousse, TUNISIA, OCT 05-07, 2015},
	pages = {109-114},
	abstract = {Automatic spell checker systems aim to verify and correct erroneous words through a suggested set of words that are the nearest lexically to the erroneous ones. However, the main disadvantage of those systems is that the wanted solution may bethe most distant lexically but the most appropriate in context. To correctly sort these solutions, the corrector must have some information about the general context of the text; the paragraph or the neighboring words of the misspelled word. In this paper, we will present an automatic spell checking method according to the context. This method is based on a learning corpus containing a distribution of the appearance probability of a word in different contexts. It combines the lexical correction via the Levenstein algorithm and the context based correction through a well definedlearning corpus which is composed of documents collected from the internet. This approach has proven efficiency and the obtained results are much more improved and satisfactory.},
	issn = {1877-0509},
	doi = {10.1016/j.procs.2015.12.055},
	author = {Nejja, Mohammed and Yousfi, Abdellah},
	editor = {Boubiche, DE and Hidoussi, F and Cruz, HT}
}
@conference { ISI:000373736100045,
	title = {Product Opinion Mining for Competitive Intelligence},
	booktitle = {INTERNATIONAL CONFERENCE ON ADVANCED WIRELESS INFORMATION AND COMMUNICATION TECHNOLOGIES (AWICT 2015)},
	series = {Procedia Computer Science},
	volume = {73},
	year = {2015},
	note = {International Conference on Advanced Wireless Information and Communication Technologies (AWICT), Natl Sch Engineers Sousse, TUNISIA, OCT 05-07, 2015},
	pages = {358-365},
	abstract = {Competitive Intelligence is one of the keys of companies Risk Management. It provides the company with a permanent lighting to its competitive environment. The increasingly frequent use of Information and Communication Technologies (ICT); including (namely) online shopping sites, blogs, social network sites, forums, provides incentives for companies check their advantages over their competitors. This information presents a new source that helps and leads the company to identify, analyze and manage the various risks associated with its business/products. Nowadays, a good use of these data helps the company to improve its products/services. In this paper, an overview of opinion mining for competitive intelligence will be presented. We{\textquoteright}ll try to synthesize the major research done for the different steps of product opinion mining. (C) 2015 The Authors. Published by Elsevier B.V.},
	issn = {1877-0509},
	doi = {10.1016/j.procs.2015.12.004},
	author = {Amarouche, Kamal and Benbrahim, Houda and Kassou, Ismail},
	editor = {Boubiche, DE and Hidoussi, F and Cruz, HT}
}
@conference { ISI:000373736100014,
	title = {Segmentation of Arabic handwritten text to lines},
	booktitle = {INTERNATIONAL CONFERENCE ON ADVANCED WIRELESS INFORMATION AND COMMUNICATION TECHNOLOGIES (AWICT 2015)},
	series = {Procedia Computer Science},
	volume = {73},
	year = {2015},
	note = {International Conference on Advanced Wireless Information and Communication Technologies (AWICT), Natl Sch Engineers Sousse, TUNISIA, OCT 05-07, 2015},
	pages = {115-121},
	abstract = {Automatic recognition of writing is among the most important axes in the NLP (Natural language processing). Several entities of different areas demonstrated the need in recognition of handwritten Arabic characters; particularly banks check processing, post office for the automation of mail sorting, the insurance for the treatment of forms and many other industries. One of the most important operations in a handwriting recognition system is segmentation. Segmentation of handwritten text is a necessary step in the development of a system of automatic writing recognition. Its goal is to try to extract all areas of the lines of the text, and this operation is made difficult in the case of handwriting, by the presence of irregular gaps or overlap between lines and fluctuations of the guidance of scripture to the horizontal. In this paper, we have developed three approaches of handwritten Arabic text segmentation, then we compared between these three approaches.},
	issn = {1877-0509},
	doi = {10.1016/j.procs.2015.12.056},
	author = {Mokhtari, Younes and Yousfi, Abdellah},
	editor = {Boubiche, DE and Hidoussi, F and Cruz, HT}
}
