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Multiple sources of information can improve knowledge mangement if they are properly combined and processed. Knowledge engineering usually relies on knowledge resources, typically ontologies. We propose a domain-independent framework which models, combines and represents heterogenous sources of information. Our aim is to build a resources repositor...
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We present GlossBoot, an effective minimally-supervised approach to acquiring wide-coverage domain glossaries for many languages. For each language of interest, given a small number of hypernymy relation seeds concerning a target domain, we bootstrap a glossary from the Web for that domain by means of iteratively acquired term/gloss extraction patt...
Citations
... These models were integrated within the proposed resources model (Thesauri entities, ontology entities, etc.); We implemented some knowledge engineering operators within a use case of merging multiple ontological and terminological resources in order to create an enriched version of WordNet [Ghoula et al. 2010a, Ghoula 2012]. ...
... Consequently, after trying different design alternatives and applying several improvements and more expressiveness in the meta-model, we propose to create a generic model that supports multiple representations for the content of a resource [Ghoula et al. 2010a]. The challenge is to create a model representing heterogeneous resources (multiple representation models) and to perform operations that involve several resources (single representation model). ...
... We have built a prototype of a lightweight repository [Ghoula et al. 2010a] using the meta-model that we described in the previous chapter. We implemented the model as a relational database because the aim of this application was to build a terminological knowledge base containing multiple terminological resources that is stored in a database. ...
Multiple tasks related to documents, such as indexing, retrieving, annotation, or translation are based on linguistic, terminological and ontological knowledge existing in resources of different types represented using various formalisms. Building bridges between these resources and using them together is a complex task. Solving this problem relies on finding the right resources before extracting the required data. Ontology repositories have been created to help in this task by collecting ontologies and offering effective indexing of these resources. However, these repositories treat a single category of resources and do not provide operations for generating new resources. To meet these needs in terms of knowledge engineering, our contributions are (1) an ontology for representing heterogeneous resources and knowledge combination operators; (2) an approach based on the principles of semantic web to ensure the representation, storage and alignment of heterogeneous resources and (3) the development of an ontology-based repository for combining alignment resources.
