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SAC
2009
ACM
15 years 6 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
PAKDD
2009
ACM
127views Data Mining» more  PAKDD 2009»
15 years 6 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...
ACL
1993
15 years 1 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
KAIS
2007
75views more  KAIS 2007»
14 years 11 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
14 years 9 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