Shadi Al Shehabi

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The main area of this paper concerns the neural methods for mapping scientific and technical information (articles, patents) and for assisting a user in carrying out the complex process of analysing large quantities of such information. In the procedure of information analysis, like in the domain of patent analysis, the complexity of the studied topics and(More)
This paper presents a first attempt for performing a precise and automatic identification of the linking behaviour in a scientific domain through the analysis of the communication of the related academic institutions on the web. The proposed approach is based on the paradigm of multiple viewpoint data analysis (MVDA) than can be fruitfully exploited to(More)
— This paper presents a new generic multi-topographic neural network model whose main area of application is clustering and knowledge extraction tasks on documentary data. The most powefull features of this model are its generalization mechanism and its mechanism of communication between topographies. This paper shows how these mechanisms can be exploited(More)
The hybridisation of different classification and mining techniques coming from different areas such as the numeric and the symbolic worlds can produce a significant enhancement of the overall classification and retrieval performance in a Data Mining or Information Retrieval context. This paper introduces an experimental methodology to match an explicative(More)