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International audience

Analysis of ancient Khmer documents can be quite challenging due to the elaborated shape of Khmer handwritten characters combined with the complex structure of how words are formed from those characters. Palm leaf manuscripts, one of the most well-known old Khmer documents, have been being digitized and centralized; therefore, document analysis functions such as text search capabilities are necessary but still remain unavailable for this type of documents. In order to contribute to the progress of relevant researches, we introduce in this paper a new dataset called SleukRith set comprising of 657 pages of Khmer palm leaf manuscripts randomly selected from various collections whose quality and digitization method are variable. The dataset contains three types of data: isolated characters, words, and lines. Each type of data is annotated with the ground truth information which is very useful for evaluating and serving as a training set for common document analysis tasks such as character/text recognition, word/line segmentation, and word spotting. In order to serve as a base line, the result of an evaluation study of Khmer isolated character recognition that we have conducted on SleukRith Set using Convolutional Neural Network is also presented.

National audience; The constraints on business process applications in terms of automation and reusability makes their development a challenging issue. To manage the variety of business process requirements, agile methods are required. Classically, business processes are implemented in a static way, what makes any evolution costly to realize. To cope with those needs, we propose the use of Web services to implement business processes. Web services and the designed business processes are stored in ontologies. An efficient multi-criteria service selection algorithm performs a semantic matching between the ontologies. It selects the most appropriate Web services among the existing ones for implementing a business process. This algorithm considers the business context, functional and QoS properties of the Web services. The user is asked for weights on QoS attributes. WordNet is integrated to solve the synonym problems. To be closer to reality and for more accurate results, our algorithm takes into account the changing values of QoS over time.

International audience; Natural language is understandable by human and not machine. None technical persons can only use natural language to specify their business requirements. However, the current version of Business process management and notation (BPMN) tools do not allow business analysts to implement their business processes without having technical skills. BPMN tool is a tool that allows users to design and implement the business processes by connecting different business tasks and rules together. The tools do not provide automatic implementation of business tasks from users' specifications in natural language (NL). Therefore, this research aims to propose a framework to automatically implement the business processes that are expressed in NL requirements. Ontology is used as a mechanism to solve this problem by comparing between users' requirements and web services' descriptions. Web service is a software module that performs a specific task and ontology is a concept that defines the relationships between different terms.