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ACM Transactions on Graphics (TOG)
A self-organizing semantic map for information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
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Knowledge Acquisition - Special issue: Current issues in knowledge modeling
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Conference Companion on Human Factors in Computing Systems
A Conceptual Modeling Approach for Semantics-Driven Enterprise Applications
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
VisSearch: a collaborative Web searching environment
Computers & Education
Improving the computer science in bioinformatics through open source pedagogy
ACM SIGCSE Bulletin
On iterative intelligent medical search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Abstraction summarization for managing the biomedical research literature
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
Search User Interfaces
Optimizing schema-last tuple-store queries in graphd
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
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Education and Information Technologies
Concept maps: integrating knowledge and information visualization
Knowledge and Information Visualization
Computer Methods and Programs in Biomedicine
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The search for truthful health information through Internet is an increasingly complex process due to the growing amount of resources. Access to information can be difficult to control even in environments where the goal pursued is well-defined, as in the case of learning activities with medical students. In this paper, we present a computer tool devised to ease the process of understanding medical concepts from information in clinical case histories. To this end, it automatically constructs concept maps and presents reliable information from different ontologies and knowledge bases. The two main components of the system are an Intelligent Information Access interface and a Concept Map Graph that retrieves medical concepts from a text input, and provides rich information and semantically related concepts. The paper includes a user evaluation of the first component and a systematic assessment for the second component. Results show that our proposal can be efficient and useful for students in a medical learning environment.