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Aiding knowledge capture by searching for extensions of knowledge models
Author(s) -
David Leake,
Ana Gabriela Maguitman,
Thomas Reichherzer,
Alberto J. Cañas,
Marco Carvalho,
Marco Arguedas,
Sofía Brenes,
Thomas C. Eskridge
Publication year - 2003
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-583-1
DOI - 10.1145/945645.945655
Subject(s) - computer science , concept map , process (computing) , domain knowledge , inference , data science , domain (mathematical analysis) , knowledge management , knowledge base , knowledge extraction , knowledge acquisition , information retrieval , world wide web , data mining , artificial intelligence , mathematical analysis , mathematics , operating system
Electronic concept mapping tools empower experts to play an active role in the knowledge capture process, and provide a medium for building richly connected multimedia knowledge models---sets of linked concept maps and resources about a particular domain. Knowledge models are intended to be used as a means for sharing knowledge among humans, not as carefully-crafted knowledge bases upon which machines will be performing inference. However, users must still confront the questions of what to include in a concept map and which concept maps to include in a knowledge model. This paper describes ongoing research on methods to provide content-based support to users as they extend concept maps by adding concepts and propositions, and as they select topics for new maps. The goal is to provide scaffolding for experts as they build their own concept maps, link their maps to others', and decide how to extend their knowledge models. The paper presents three approaches which start from a concept map under construction and mine related information---both from prior concept maps, and from the web---to propose information to aid the user's knowledge capture and knowledge construction. The paper begins with a brief summary of the concept mapping process and the CmapTools concept mapping software. It then presents three types of implemented suggesters, to suggest concepts, propositions, concept maps, and new topics to aid experts using the CmapTools, and describes preliminary experiments to assess their performance. It closes with a discussion of next steps for testing and refining these methods.

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