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ICDE
2012
IEEE
227views Database» more  ICDE 2012»
13 years 6 months ago
Horizontal Reduction: Instance-Level Dimensionality Reduction for Similarity Search in Large Document Databases
—Dimensionality reduction is essential in text mining since the dimensionality of text documents could easily reach several tens of thousands. Most recent efforts on dimensionali...
Min-Soo Kim 0001, Kyu-Young Whang, Yang-Sae Moon
132
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IPM
2007
145views more  IPM 2007»
15 years 3 months ago
Text mining techniques for patent analysis
Patent documents contain important research results. However, they are lengthy and rich in technical terminology such that it takes a lot of human efforts for analyses. Automatic...
Yuen-Hsien Tseng, Chi-Jen Lin, Yu-I Lin
130
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FLAIRS
2006
15 years 5 months ago
Using Web Searches on Important Words to Create Background Sets for LSI Classification
The world wide web has a wealth of information that is related to almost any text classification task. This paper presents a method for mining the web to improve text classificati...
Sarah Zelikovitz, Marina Kogan
144
Voted
BMCBI
2008
184views more  BMCBI 2008»
15 years 3 months ago
Integrating protein-protein interactions and text mining for protein function prediction
Background: Functional annotation of proteins remains a challenging task. Currently the scientific literature serves as the main source for yet uncurated functional annotations, b...
Samira Jaeger, Sylvain Gaudan, Ulf Leser, Dietrich...
126
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CIKM
2010
Springer
15 years 2 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...