ACL RD-TEC 1.0 Summarization of C02-1103
Paper Title:
AUTOMATIC TEXT CATEGORIZATION USING THE IMPORTANCE OF SENTENCES
AUTOMATIC TEXT CATEGORIZATION USING THE IMPORTANCE OF SENTENCES
Authors: Youngjoong Ko and Jinwoo Park and Jungyun Seo
Primarily assigned technology terms:
- automatic text categorization
- categorization
- classification
- classifier
- classifiers
- feature extraction
- feature selection
- indexing
- information retrieval
- k-nn
- learning
- learning algorithms
- machine learning
- macro-averaging
- measuring
- micro-averaging method
- naive bayes
- optimization
- parameter optimization
- statistical feature selection
- statistical methods
- summarization
- supervised learning
- support vector machines
- svm classifier
- svm light
- text categorization
- text categorization system
- text classification
- text representation
- text summarization
- validation
- vector space model
Other assigned terms:
- ambiguity
- case
- categorization task
- clusters
- cohesion
- convergence
- data set
- data sets
- document
- document frequency
- document vector
- document vectors
- empirical evaluation
- empirical results
- experimental results
- extraction process
- f measure
- feature
- inverted document frequency
- linguistic
- meaning
- measure
- measures
- method
- precision
- process
- running time
- sentence
- sentence importance
- sentences
- statistics
- stop word list
- structural information
- style
- support vector
- technique
- term
- term frequency
- terms
- test data
- text
- text documents
- training
- training data
- training data set
- training phase
- vector space
- vocabulary
- word
- words
