Semantic Web Search System Founded on Case-Based Reasoning and Ontology Learning

Author(s):  
Hajer Baazaoui-Zghal ◽  
Nesrine Ben Mustapha ◽  
Manel Elloumi-Chaabene ◽  
Antonio Moreno ◽  
David Sanchez
2013 ◽  
Vol 28 (4) ◽  
pp. 425-449 ◽  
Author(s):  
Mathieu d'Aquin ◽  
Jean Lieber ◽  
Amedeo Napoli

AbstractThis article presents the Kasimir system dedicated to decision knowledge management in oncology and which is built on top of Semantic Web technologies, taking benefit from standard knowledge representation formalisms and open reasoning tools. The representation of medical decision protocols, in particular for breast cancer treatment, is based on concepts and instances implemented within the description logic OWL DL (Web ontology language description logic). The knowledge units related to a protocol can then be applied for solving specific medical problems, using instance or concept classification. However, the straight application of a protocol is not always satisfactory, for example, because of contraindications, necessitating an adaptation of the protocol. This is why the principles and methods of case-based reasoning (CBR) in the framework of DLs have been used. In addition, the domain of oncology is complex and involves several specialties, for example, surgery and chemotherapy. This complexity can be better undertaken with a viewpoint-based representation of protocols and viewpoint-based reasoning, for either application or adaptation of the protocols. Accordingly, a distributed DL has been used for representing a viewpoint-based protocol. The application and the adaptation of the viewpoint-based protocol to medical cases is carried out using global instance classification and decentralized CBR.


Author(s):  
Dhavalkumar Thakker ◽  
Taha Osman ◽  
David Al-Dabass

Web service development is encouraging scenarios where individual or integrated application services can be seamlessly and securely published on the Web without the need to expose their implementation details. However, as Web services proliferate, it becomes difficult to matchmake and integrate them in response to users requests. The goal of our research is to investigate the utilization of the Semantic Web in building a developer-transparent framework facilitating the automatic discovery and composition of Web services. In this chapter, we present a Semantic Case Based Reasoner (SCBR) framework that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and composition. Our approach is original as it considers the runtime behaviour of a service resulting from its execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. To facilitate Web services composition, we extend our fundamental discovery and matchmaking algorithm using a light-weight knowledge-based substitution approach to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on the Constraint Satisfaction Problem (CSP).


Author(s):  
Mathieu d’Aquin ◽  
Jean Lieber ◽  
Amedeo Napoli

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