Bo-Yeong Kang

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Traditional index weighting approaches for information retrieval from texts depend on the term frequency based analysis of the text contents. A shortcoming of these indexing schemes, which consider only the occurrences of the terms in a document, is that they have some limitations in extracting semantically exact indexes that represent the semantic content(More)
Clinical Practice Guidelines (CPGs) play an important role in improving the quality of care and patient outcomes. Although several machine-readable representations of practice guidelines implemented with semantic web technologies have been presented, there is no implementation to represent uncertainty with respect to activity graphs in clinical practice(More)
Current approaches to index weighting for information retrieval from texts are based on statistical analysis of the texts’ contents. A key shortcoming of these indexing schemes, which consider only the terms in a document, is that they cannot extract semantically exact indexes that represent the semantic content of a document. To address this issue, we(More)
SUMMARY Despite the importance of using the semantic distance to improve the performance of conventional expression-based clustering, there are few freely available software that provides a clustering algorithm using the ontology-based semantic distances as prior knowledge. Here, we present the SICAGO (SemI-supervised Cluster Analysis using semantic(More)