Skip to main navigation
Skip to search
Skip to main content
University of Haifa Home
Update your profile
Link opens in a new tab
Search content at University of Haifa
Home
Researchers
Research units
Research output
Distributional word clusters vs. words for text categorization
Ron Bekkerman
, Ran El-Yaniv
, Naftali Tishby
, Yoad Winter
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Distributional word clusters vs. words for text categorization'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Word Clusters
100%
Text Categorization
100%
Support Vector Machine
60%
Cluster Representation
60%
Word-based
40%
Compact Representation
20%
High Performance
20%
Efficient Representation
20%
Support Vector Machine Classifier
20%
Structural Difference
20%
Novel Combinations
20%
Distributional Clustering
20%
20 Newsgroups
20%
WebKB
20%
Information Bottleneck
20%
Bag-of-words Representation
20%
Reuters-21578
20%
Computer Science
Support Vector Machine
100%
Text Categorization
100%
Compact Representation
25%
Efficient Representation
25%
Mathematics
Support Vector Machine
100%
Text Categorization
100%