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Non-negative Matrix Factorization (NMF, [5]) and Probabilistic Latent Semantic Analysis (PLSA, [4]) have been successfully applied to a number of text analysis tasks such as docum...
Computational resources for research in legal environments have historically implied remote access to large databases of legal documents such as case law, statutes, law reviews an...
Jack G. Conrad, Khalid Al-Kofahi, Ying Zhao, Georg...
The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one ...
Document clustering has been used for better document retrieval, document browsing, and text mining in digital library. In this paper, we perform a comprehensive comparison study ...
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Document clustering has been used as a core technique in managing vast amount of data and providing needed information. In on-line environments, generally new information gains mo...
Document clustering has been used for better document retrieval, document browsing, and text mining. In this paper, we investigate if biomedical ontology MeSH improves the cluster...
This paper introduces a new technique of document clustering based on frequent senses. The proposed system, GDClust (Graph-Based Document Clustering) works with frequent senses ra...
Recent research shows that ontology as background knowledge can improve document clustering quality with its concept hierarchy knowledge. Previous studies take term semantic simila...
Xiaodan Zhang, Liping Jing, Xiaohua Hu, Michael K....
Wikipedia has been applied as a background knowledge base to various text mining problems, but very few attempts have been made to utilize it for document clustering. In this pape...
Anna Huang, David N. Milne, Eibe Frank, Ian H. Wit...