A document retrieval model based on term frequency ranks
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Navigation via similarity: automatic linking based on semantic closeness
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
Four Paradigms for Indexing Video Conferences
IEEE MultiMedia
Inter-patient distance metrics using SNOMED CT defining relationships
Journal of Biomedical Informatics
Computers in Biology and Medicine
Measures of semantic similarity and relatedness in the biomedical domain
Journal of Biomedical Informatics
Measuring concept relatedness using language models
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A Hybrid Approach to Improving Automatic Speech Recognition Via NLP
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
A System for Ontology-Based Annotation of Biomedical Data
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
A review of auditing methods applied to the content of controlled biomedical terminologies
Journal of Biomedical Informatics
Measuring semantic similarity between biomedical concepts within multiple ontologies
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
Computing Knowledge-Based Semantic Similarity from the Web: An Application to the Biomedical Domain
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Automated identification of synonyms in biomedical acronym sense inventories
Louhi '10 Proceedings of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
An ontology-based measure to compute semantic similarity in biomedicine
Journal of Biomedical Informatics
Towards a framework for developing semantic relatedness reference standards
Journal of Biomedical Informatics
Journal of Biomedical Informatics
A hybrid knowledge-based and data-driven approach to identifying semantically similar concepts
Journal of Biomedical Informatics
Employing UMLS for generating hints in a tutoring system for medical problem-based learning
Journal of Biomedical Informatics
Journal of Biomedical Informatics
ONCO-i2b2: improve patients selection through case-based information retrieval techniques
DILS'12 Proceedings of the 8th international conference on Data Integration in the Life Sciences
An evaluation of corpus-driven measures of medical concept similarity for information retrieval
Proceedings of the 21st ACM international conference on Information and knowledge management
UAHCI'13 Proceedings of the 7th international conference on Universal Access in Human-Computer Interaction: applications and services for quality of life - Volume Part III
Evaluating measures of semantic similarity and relatedness to disambiguate terms in biomedical text
Journal of Biomedical Informatics
Determining the difficulty of Word Sense Disambiguation
Journal of Biomedical Informatics
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The objective of this work is to investigate the feasibility of conceptual similarity metrics in the framework of the Unified Medical Language System (UMLS). We have investigated an approach based on the minimum number of parent links between concepts, and evaluated its performance relative to human expert estimates on three sets of concepts for three terminologies within the UMLS (i.e., MeSH, ICD9CM, and SNOMED). The resulting quantitative metric enables computer-based applications that use decision thresholds and approximate matching criteria. The proposed conceptual matching supports problem solving and inferencing (using high-level, generic concepts) based on readily available data (typically represented as low-level, specific concepts). Through the identification of semantically similar concepts, conceptual matching also enables reasoning in the absence of exact, or even approximate, lexical matching. Finally, conceptual matching is relevant for terminology development and maintenance, machine learning research, decision support system development, and data mining research in biomedical informatics and other fields.