Abstract. In this paper the C-CLASSIC Description Logic is used to design the retrieval and selection tasks of a Case-Based Reasoning system with homogeneous, explicit and formal criteria. The case base is organized by means of a taxonomy of index concepts. Case retrieval is performed using the automatic concept classification of the description logic. Case selection is performed using two criteria: similarity and dissimilarity. Similaritybetween two cases is characterized by the most specific concept which subsumes the two cases (Least Common Subsumer or LCS), and dissimilarity by a concept representing properties which belong to one case but not to the other. A partial order induced by the subsumption relationship on these concepts is used to select the most similar cases.
This paper highlights the benefit of semantic information retrieval in legal networks. User queries get more complex when they combine constraints on semantic content and intertextual links between documents. Comparing two methods of search in legal collection networks, we present new functionalities of search and browsing. Relying on a structured representation of the collection graph, the first approach allows for approximate answers and knowledge discovery. The second one supports richer semantics and scalability but offers fewer search functionalities. We indicate how those approaches could be combined to get the best of both.
In the information retrieval (IR) domain a collection of documents is represented as a set of documents where cross references between documents are usually not taken into account in the querying process. This standard document model is not tailored to legal professional uses where the context of interpretation is crucial. Existing access tools do not take into account the complexity of references between legal documents. XML based standards have been created to facilitate access and management of legal data. Their exploitation for IR purposes offers new possibilities for advanced search techniques. In this work, we propose a novel approach allowing to exploit the XML standard formats of legal documents to query a collection of related documents and return relevant answers to the end-user. We consider exploiting at the same time the semantic content of the documents and their interrelationships using Formal and Relational Concept Analysis. Answers are presented as documents or graphs of interlinked documents.
This article presents the contribution of the LIPN : Laboratoire d'Informatique de Paris Nord (France) to the NLQ2NEXI (Natural Language Queries to NEXI) task (part of the Natural Language Processing (NLP) track) of the Initiative for Evaluation of XML Retrieval (INEX 2006). It discusses the use of shallow parsing methods to analyse natural language queries.
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