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AIRS
2006
Springer
14 years 4 months ago
Natural Document Clustering by Clique Percolation in Random Graphs
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
Wei Gao, Kam-Fai Wong
SIGIR
1998
ACM
14 years 4 months ago
Web Document Clustering: A Feasibility Demonstration
Users of Web search engines are often forced to sift through the long ordered list of document “snippets” returned by the engines. The IR community has explored document cluste...
Oren Zamir, Oren Etzioni
CIKM
2000
Springer
14 years 4 months ago
A Semi-Supervised Document Clustering Technique for Information Organization
This paper discusses a new type of semi-supervised document clustering that uses partial supervision to partition a large set of documents. Most clustering methods organizes docum...
Han-joon Kim, Sang-goo Lee
SIGIR
2000
ACM
14 years 4 months ago
An investigation of linguistic features and clustering algorithms for topical document clustering
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
SIGIR
2003
ACM
14 years 5 months ago
Document clustering based on non-negative matrix factorization
In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
Wei Xu, Xin Liu, Yihong Gong
IRAL
2003
ACM
14 years 5 months ago
Improving document clustering by utilizing meta-data
In this paper, we examine how to improve the precision and recall of document clustering by utilizing meta-data. We use meta-data through NewsML tags to assist clustering and show...
Kam-Fai Wong, Nam-Kiu Chan, Kam-Lai Wong
IRAL
2003
ACM
14 years 5 months ago
Keyword-based document clustering
1 Document clustering is an aggregation of related documents to a cluster based on the similarity evaluation task between documents and the representatives of clusters. Terms and t...
Seung-Shik Kang
SIGIR
2004
ACM
14 years 5 months ago
Document clustering via adaptive subspace iteration
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
Tao Li, Sheng Ma, Mitsunori Ogihara
WEBI
2005
Springer
14 years 6 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
IJCNLP
2005
Springer
14 years 6 months ago
Document Clustering with Grouping and Chaining Algorithms
Document clustering has many uses in natural language tools and applications. For instance, summarizing sets of documents that all describe the same event requires first identifyi...
Yllias Chali, Soufiane Noureddine