Conference proceeding
Integrating biomedical literature clustering and summarization approaches using biomedical ontology
Proceedings of the 1st international workshop on text mining in bioinformatics
10 Nov 2006
Abstract
We introduce a method that integrates biomedical literature clustering and summarization using biomedical ontology. The core of the approach is to identify document cluster models as semantic chunks capturing the core semantic relationships in the ontology-enriched scale-free graphical representation of documents. These document cluster models are used for both document clustering on document assignment and text summarization on the construction of Text Semantic Interaction Network (TSIN). Our experimental results show our approach is superior to traditional approaches including Bisecting K-means as a leading document clustering approach in terms of cluster quality and clustering reliability. In addition, our approach provides concise but rich text summary in key concepts and sentences.
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1 citations in Scopus
Details
- Title
- Integrating biomedical literature clustering and summarization approaches using biomedical ontology
- Creators
- Illhoi YooXiaohua HuIl-Yeol Song
- Publication Details
- Proceedings of the 1st international workshop on text mining in bioinformatics
- Conference
- 1st international workshop on text mining in bioinformatics, 1st
- Series
- TMBIO '06
- Publisher
- Association for Computing Machinery (ACM)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-34547683822
- Other Identifier
- 991014878745304721