Conference proceeding
A comparative study of ontology based term similarity measures on PubMed document clustering
ADVANCES IN DATABASES: CONCEPTS, SYSTEMS AND APPLICATIONS, Vol.4443
Lecture Notes in Computer Science
01 Jan 2007
Abstract
Recent research shows that ontology as background knowledge can improve document clustering quality with its concept hierarchy knowledge. Previous studies take term semantic similarity as an important measure to incorporate domain knowledge into clustering process such as clustering initialization and term re-weighting. However, not many studies have been focused on how different types of term similarity measures affect the clustering performance for a certain domain. In this paper, we conduct a comparative study on how different semantic similarity measures of term including path based similarity measure, information content based similarity measure and feature based similarity measure affect document clustering. We evaluate term re-weighting as an important method to integrate domain ontology to clustering process. Meanwhile, we apply k-means clustering on one real-world text dataset, our own corpus generated from PubMed. Experiment results on 8 different semantic measures have shown that: (1) there is no a certain type of similarity measures that significantly outperforms the others; (2) Several similarity measures have rather more stable performance than the others; (3) term re-weighting has positive effects on medical document clustering, but might not be significant when documents are short of terms.
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Details
- Title
- A comparative study of ontology based term similarity measures on PubMed document clustering
- Creators
- Xiaodan Zhang - Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut, Philadelphia, PA 19104 USALiping Jing - Univ Hong Kong, ETI, Dept Math, Hong Kong, Peoples R ChinaXiaohua Hu - Drexel UniversityMichael Ng - Hong Kong Baptist Univ, Dept Matemat, Kowloon, Peoples R ChinaXiaohua Zhou - Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut, Philadelphia, PA 19104 USA
- Contributors
- R Kotagiri (Editor)P R Krishna (Editor)M Mohania (Editor)E Nantajeewarawat (Editor)
- Publication Details
- ADVANCES IN DATABASES: CONCEPTS, SYSTEMS AND APPLICATIONS, Vol.4443
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 3
- Grant note
- 240205; 240196 / PA Dept of Health Tobacco Settlement Formula 239667 / PA Dept of Health NSF IIS 0448023; NSF CCF 0514679 / NSF; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019170396804721
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- Domestic collaboration
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Theory & Methods