Maria Vargas-Vera

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An important precondition for realizing the goal of a semantic web is the ability to annotate web resources with semantic information. In order to carry out this task, users need appropriate representation languages, ontologies, and support tools. In this paper we present MnM, an annotation tool which provides both automated and semi-automated support for(More)
This paper describes a Semantic Annotation Tool for extraction of knowledge structures from web pages through the use of simple user-defined knowledge extraction patterns. The semantic annotation tool contains: an ontology-based mark-up component which allows the user to browse and to mark-up relevant pieces of information; a learning component (Crystal(More)
This paper describes a system which recognizes events on news stories. Our system classifies stories and populates a hand-crafted ontology with new instances of classes defined in it. Currently, our system recognizes events which can be classified as belonging to a single category and it also recognizes overlapping events within one article (more than one(More)
This paper describes a system for semi-automatic population of ontologies with instances from unstructured text. It is based on supervised learning, learns extraction rules from annotated text and then applies those rules on new articles to populate the ontology. Hence, the system classifies stories and populates a hand-crafted ontology with new instances.(More)
The use of the web has become popular and also the need of services that could exploit the vast amount of information in it. Therefore, there is a need for automated question answering systems. These kind of systems should allow users to ask questions in everyday language and receive an answer quickly and with a context which allows the user to validate the(More)