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SAC
2009
ACM
15 years 10 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
121
Voted
PAKDD
2009
ACM
127views Data Mining» more  PAKDD 2009»
15 years 10 months ago
Clustering Documents Using a Wikipedia-Based Concept Representation
Abstract. This paper shows how Wikipedia and the semantic knowledge it contains can be exploited for document clustering. We first create a concept-based document representation b...
Anna Huang, David N. Milne, Eibe Frank, Ian H. Wit...
134
Voted
ACL
1993
15 years 5 months ago
Towards the Automatic Identification of Adjectival Scales: Clustering Adjectives According to Meaning
In this paper we present a method to group adjectives according to their meaning, as a first step towards the automatic identification of adjectival scales. We discuss the propert...
Vasileios Hatzivassiloglou, Kathleen McKeown
143
Voted
KAIS
2007
75views more  KAIS 2007»
15 years 3 months ago
Non-redundant data clustering
Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice this discovery process should avoid redundancies with existi...
David Gondek, Thomas Hofmann
EMNLP
2009
15 years 1 months ago
Clustering to Find Exemplar Terms for Keyphrase Extraction
Keyphrases are widely used as a brief summary of documents. Since manual assignment is time-consuming, various unsupervised ranking methods based on importance scores are proposed...
Zhiyuan Liu, Peng Li, Yabin Zheng, Maosong Sun