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» A Semi-Supervised Document Clustering Algorithm Based on EM
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SIGIR
2008
ACM
15 years 1 months ago
Enhancing text clustering by leveraging Wikipedia semantics
Most traditional text clustering methods are based on "bag of words" (BOW) representation based on frequency statistics in a set of documents. BOW, however, ignores the ...
Jian Hu, Lujun Fang, Yang Cao, Hua-Jun Zeng, Hua L...
KAIS
2006
164views more  KAIS 2006»
15 years 1 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
ICDAR
2011
IEEE
14 years 1 months ago
A New Fourier-Moments Based Video Word and Character Extraction Method for Recognition
— This paper presents a new method based on Fourier and moments features to extract words and characters from a video text line in any direction for recognition. Unlike existing ...
Deepak Rajendran, Palaiahnakote Shivakumara, Bolan...
SIGIR
2011
ACM
14 years 4 months ago
Cluster-based fusion of retrieved lists
Methods for fusing document lists that were retrieved in response to a query often use retrieval scores (or ranks) of documents in the lists. We present a novel probabilistic fusi...
Anna Khudyak Kozorovitzky, Oren Kurland
ICASSP
2009
IEEE
14 years 11 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...