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With the fast growing development of the Web, the adoption of ontologies to improve the exploitation of information resources, is already heralded as a promising model of representation. However, the relevance of information that they contain requires regular updating, and specifically, the addition of new knowledge. Recently, new research approaches were defined in order to automatically enrich ontology...
Situation awareness is a promising approach to recommend to a mobile user the most suitable resources for a specific situation. However, determining the correct user situation is not a simple task since users have different habits that may affect the way in which the situations arise. Thus, an appropriate tuning aimed at adapting the situation recognizer to the specific user is desirable to make a...
Research on the future of the Egyptian tourism industry has become the subject of countless studies and debates. Different wildcards have high impacts on this crucial industry and ultimately of the future of the Egyptian national income. This paper is about an Intelligent Decision Support System (DSS) that specifically focuses on assessing the impacts of wildcards on the future revenues of the Egyptian...
In group decision making problems is common the necessity of achieving a consensus before making a decision. Many consensus reaching processes have been introduced in the literature but not many intelligent systems have finally been implemented to deal with such processes. In this contribution an initial prototype of a consensus support system supported on a multi-agent paradigm is presented, showing...
In this work, we propose an approach of thematisation of audiovisual (AV) documents for a research according to topics evoked in each document. The first step of our approach is to define the descriptive metadata allowing a bibliographical description of the whole documents. The second step is divided into three stages: the first one is a temporal segmentation, the second one is space segmentation...
The constant growth of the Internet has made recommender systems very useful to guide users coping with a large amount of data. In this paper, we present a domain independent collaborative and semantic-based recommender system which uses distinct and complementary modules. The approach targets users with various interests and is based on: (i) a collaborative module using association rules in order...
Current semantic recommender systems aim to exploit the website ontologies to produce valuable web recommendations. However, Web usage knowledge for recommendation is presented separately and differently from the domain ontology, this leads to the complexity of using inconsistent knowledge resources. This paper aims to solve this problem by proposing a novel ontology-style model of Web usage to represent...
Nowadays, satisfying user needs has become the main challenge in a variety of web applications. Recommender systems play a major role in that direction. However, as most of the information is present in a textual form, recommender systems face the challenge of efficiently analyzing huge amounts of text. The usage of semantic-based analysis has gained much interest in recent years. The emergence of...
The paper is devoted to intelligent matching ontological subgraphs to concepts. The problem is considered from the point of view of rough set theory. An accuracy of approximation determines how far in a semantic space it is from a given ontological subgraph to a given concept. The approach presented in the paper can be applied to intelligent searching of a bibliographical data base for abstracts semantically...
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