Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Optimization of inverted vector searches
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Document clustering using word clusters via the information bottleneck method
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Information Retrieval
Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Frequent term-based text clustering
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
An Adaptive Meta-Clustering Approach: Combining the Information from Different Clustering Results
CSB '02 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Document clustering by concept factorization
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Document clustering via adaptive subspace iteration
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A comprehensive comparison study of document clustering for a biomedical digital library MEDLINE
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Attempt to design a bio-medical knowledge discovery system
International Journal of Bio-Inspired Computation
A Unified Architecture for Biomedical Search Engines Based on Semantic Web Technologies
Journal of Medical Systems
| Hi-index | 0.00 |
Document clustering has been used for better document retrieval and text mining. In this paper, we investigate if a biomedical ontology improves biomedical literature clustering performance in terms of the effectiveness and the scalability. For this investigation, we perform a comprehensive comparison study of various document clustering approaches such as hierarchical clustering methods, Bisecting K-means, K-means and Suffix Tree Clustering (STC). According to our experiment results, a biomedical ontology significantly enhances clustering quality on biomedical documents. In addition, our results show that decent document clustering approaches, such as Bisecting K-means, K-means and STC, gains some benefit from the ontology while hierarchical algorithms showing the poorest clustering quality do not reap the benefit of the biomedical ontology.