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Section: New Software and Platforms
Knowledge Systems in Health and Cooking
The Kasimir System for Decision Knowledge Management
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Keywords: Classification-based reasoning, case-based reasoning, decision knowledge management, knowledge edition, knowledge base maintenance, semantic portal
Functional Description.
The objective of the Kasimir system is decision support and knowledge management for the treatment of cancer. A number of modules have been developed within the Kasimir system for editing treatment protocols, visualization, and maintenance. Kasimir is developed within a semantic portal, based on OWL. KatexOWL (Kasimir Toolkit for Exploiting OWL Ontologies, http://katexowl.loria.fr ) was developed in a generic way and is applied to Kasimir. In particular, the user interface EdHibou of KatexOWL is used for querying the protocols represented within the Kasimir system. In [86] , this research is presented, together with an extension of Kasimir for multi-viewpoint case-based reasoning.
CabamakA (case base mining for adaptation knowledge acquisition) is a module of the Kasimir system. This system performs case base mining for adaptation knowledge acquisition and provides information units to be used for building adaptation rules. Actually, the mining process in CabamakA is based on a frequent close itemset extraction module from the Coron platform (see § 6.1.1 ).
The Oncologik system is a collaborative editing tool aiming at facilitating the management of medical guidelines. Based on a semantic wiki, it allows the acquisition of formalized decision knowledge also includes a graphical decision tree editor called KcatoS. A version of Oncologik was released in 2012 (http://www.oncologik.fr/ ).
Taaable: a System for Retrieving and Creating New Cooking Recipes by Adaptation
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Keywords: Knowledge acquisition, ontology engineering, semantic annotation, case-based reasoning, hierarchical classification, text mining.
Functional Description.
The objectives of the Taaable system are to retrieve textual cooking recipes and to adapt these retrieved recipes whenever needed [84] . Suppose that someone is looking for a “leek pie” but has only an “onion pie” recipe: how can the onion pie recipe be adapted?
The Taaable system combines principles, methods, and technologies such as case-based reasoning (CBR), ontology engineering, text mining, text annotation, knowledge representation, and hierarchical classification. Ontologies for representing knowledge about the cooking domain, and a terminological base for binding texts and ontology concepts, were built from textual web resources. These resources are used by an annotation process for building a formal representation of textual recipes. A CBR engine considers each recipe as a case, and uses domain knowledge for reasoning, especially for adapting an existing recipe w.r.t. constraints provided by the user, holding on ingredients and dish types.
The Taaable system is available on line since 2008 at http://intoweb.loria.fr/taaable3ccc/ , and is constantly evolving. Since 2014, Taaable is based on Tuuurbine, a generic ontology guided CBR engine over RDFS, and Revisor, an adaptation engine implementing various revision operators. This year, new features have been added to the Taaable system in order to address the new challenges of the 8th Computer Cooking Contest at ICCBR 2015. Firstly, FCA was used to improve the ingredient substitution, by taking into account ingredient combinations in a large set of recipes. Secondly, an approach based on mixed linear optimization has been used to adapt ingredient quantities, in order to be more realistic with a real cooking setting.
Tuuurbine: a Generic Ontology Guided Case-Based Inference Engine
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Keywords: case-based reasoning, inference engine, knowledge representation, ontology engineering, semantic web
Functional Description.
The experience acquired since 5 years with the Taaable system conducted to the creation of a generic cased-based reasoning system, whose reasoning procedure is based on a domain ontology [91] . This new system, called Tuuurbine (http://tuuurbine.loria.fr/ ), takes into account the retrieval step, the case base organization, and also an adaptation procedure which is not addressed by other generic case-based reasoning tools. Moreover, Tuuurbine is built over semantic web standards that will ensure facilities for being plugged over data available on the web. The domain knowledge is represented in an RDF store, which can be interfaced with a semantic wiki, for collaborative edition and management of the knowledge involved in the reasoning system (cases, ontology, adaptation rules). The development of Tuuurbine was supported by an Inria ADT funding until October 2013.
BeGoood: a Generic System for Managing Non-Regression Tests on Knowledge Bases
Functional Description.
BeGoood is a system allowing to define test plans, independent of any application domain, and usable for testing any system answering queries by providing results in the form of sets of strings. BeGoood provides all the features usually found in test systems, such as tests, associated queries, assertions, and expected result sets, test plans (sets of tests) and test reports. The system is able to evaluate the impact of a system modification by running again test plans and by evaluating the assertions which define whether a test fails or succeeds. BeGoood is used by the Taaable system for managing the evolution of the knowledge base used by the CBR system.
Revisor: a Library of Revision Operators and Revision-Based Adaptation Operators
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Keywords: Belief revision, adaptation, revision-based adaptation, case-based reasoning, inference engines, knowledge representation.
Functional Description.
Revisor is a library of inference engines dedicated to belief revision and to revision-based adaptation for case-based reasoning. It is open source, under a GPL license and available on the web (http://revisor.loria.fr/ ). It gathers several engines developed during the previous years for various knowledge representation formalisms (propositional logic, with or without the use of adaptation knowledge, conjunction of linear constraints, and qualitative algebras [89] ). Some of these engines are already used in the Taaable system. Current developments on Revisor aim at defining new engines in other formalisms. In particular, a study on a revision operator in the propositional closure of linear constraints (with integer and real number variables) has been carried out [70] : definition, properties and algorithm.