CORR
2010
Springer
13 years 11 months ago
2010
Springer
As the amount of online text increases, the demand for text classification to aid the analysis and management of text is increasing. Text is cheap, but information, in the form of...
SIGIR
2010
ACM
13 years 11 months ago
2010
ACM
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
PRIS
2004
14 years 27 days ago
2004
Abstract. The number of features to be considered in a text classification system is given by the size of the vocabulary and this is normally in the range of the tens or hundreds o...
CLIN
2001
14 years 28 days ago
2001
This paper investigates the use of stemming for classification of Dutch (email) texts. We introduce a stemmer, which combines dictionary lookup (implemented efficiently as a finit...
CASCON
2001
14 years 28 days ago
2001
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
FLAIRS
2006
14 years 28 days ago
2006
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...
FLAIRS
2004
14 years 28 days ago
2004
We illustrate that Web searches can often be utilized to generate background text for use with text classification. This is the case because there are frequently many pages on the...
DMIN
2006
14 years 28 days ago
2006
Abstract-- Text classification or categorization is a conventional classification problem applied to the text domain. In the cases when statistical classification methods are used,...
ICMLA
2008
14 years 29 days ago
2008
Standard Machine Learning approaches to text classification use the bag-of-words representation of documents to deceive the classification target function. Typical linguistic stru...
ECIR
2008
Springer
14 years 1 months ago
2008
Springer
Abstract. This paper investigates a new extension of the Probabilistic Latent Semantic Analysis (PLSA) model [6] for text classification where the training set is partially labeled...