Arabic dialects have no standard dialectal spelling systems. Arbitrary transcription of dialect words will display varieties of orthographic forms. This causes problems for natural language processing (NLP). In this paper, we present an automatic process for normalization of spontaneously spelled Tunisian Arabic (TA) into a conventional orthography CODA-TA [1]. We show that rule-based and statistical methods can reduce the transcription errors by 77.73% over this baseline on an unseen test set.

With the increasing number of Web services, the personalized recommendation of Web services has become more and more important. Fortunately, the social network popularity nowadays brings a good alternative for social recommendation to avoid the data sparsity problem that is not treated very well in the collaborative filtering approach. Since the social network provides a big data about the users, the trust concept has become necessary to filter this abundance and to foster the successful interactions between the users. In this paper, we firstly propose a trusted friend detection mechanism in a social network. The dynamic of the users’ interactions over time and the similarity of their interests have been considered. Secondly, we propose a Web service social recommendation mechanism which considers the expertise of the trusted friends according to their past invocation histories and the active user’s query. The experiments of each mechanism produced satisfactory results.

Hidden Markov Models (HMM) are currently widely used in Automatic Speech Recognition (ASR) as being the most effective models. Yet, they sometimes pose some problems of discrimination. The hybridization of Artificial Neural Networks(ANN) in particular Multi Layer Perceptrons (MLP) with HMM is a promising technique to overcome these limitations. In order to ameliorate results of recognition system, we use Support Vector Machines (SVM) witch characterized by a high predictive power and discrimination. The incorporation of SVM with HMM brings into existence of the new system of ASR. So,

This work addresses the Interaction Protocols (IP) adaptation issue for coordination in the context of Crisis Management Processes (CMP). CMP refers to the coordination of different activities performed by involved actors in a dy-namic and unstable context. Using interaction protocols (such as contract net, negotiation or vote) is one possible way to deal with this coordination. In order to guarantee an efficient use of IP, we need to adapt them. In our previous work, we proposed an MDA (Model Driven Architecture) framework to support the IP adaptation. More precisely, we proposed the conjointly use of version and context notions to model the IP versions and their contexts (the CIM level). We also pro-posed an extension of AUML sequence diagram meta-model to specify graph-ically the contextualized versioned interaction protocols (the PIM level). In this paper, we propose an Interaction Protocols Adaptation and Management System (IPAMS) that supports the previous contributions. This IPAMS ensures the IP adaptation at run time. Finally, we propose a well-known crisis scenario called “Air Crash Management Process” in order to illustrate the proposed solution.