Results 251 to 260 of about 346,822 (289)

Exploiting Hierarchy in Text Categorization

Information Retrieval, 1999
With the recent dramatic increase in electronic access to documents, text categorization—the task of assigning topics to a given document—has moved to the center of the information sciences and knowledge management. This article uses the structure that is present in the semantic space of topics in order to improve performance in text categorization ...
Andreas S. Weigend, Erik D. Wiener, Jan O. Pedersen   +2 more
openaire   +1 more source

Categorical Document Frequency Based Feature Selection for Text Categorization

2011 International Conference of Information Technology, Computer Engineering and Management Sciences, 2011
Effective feature selection methods are essential for improving the accuracy and efficiency of text categorization. Motivated by document frequency, we proposed a new filter-based feature selection approach, called categorical document frequency. The categorical document frequency displays the distribution of a term over each category.
Zhilong Zhen, Haijuan Wang, Lixin Han, Zhan Shi   +3 more
openaire   +1 more source

Text Categorization: Implementation

2018
This chapter is concerned with the implementation of the prototype version of the text categorization system in Java.
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Automatic text categorization: case study

VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings., 2003
Text categorization is a process of classifying documents with regard to a group of one or more existent categories according to themes or concepts present in their contents. The most common application of it is in information retrieval systems (IRS) to document indexing.
R.F. Correa, T.B. Ludermir
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On-line handwritten text categorization

SPIE Proceedings, 2009
As new innovative devices, accepting or producing on-line documents, emerge, managing facilities for these kinds of documents such as topic spotting are required. This means that we should be able to perform text categorization of on-line documents. The textual data available in on-line documents can be extracted through online recognition, a process ...
Peña Saldarriaga, Sebastián, Viard-Gaudin, Christian, Morin, Emmanuel   +2 more
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Categorization of news articles using neural text categorizer

2009 IEEE International Conference on Fuzzy Systems, 2009
This research proposes the application of NTC (Neural Text Categorizer) for categorizing news articles. Even if the research on text categorization has been progressed very much, documents should be still encoded into numerical vectors. Encoding so causes the two main problems: huge dimensionality and sparse distribution.
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Automatic text categorization using NTC

2009 First International Conference on Networked Digital Technologies, 2009
In this research, we propose NTC (Neural Text Categorizer) as the approach to text categorization. Traditional approaches to text categorization require encoding documents into numerical vectors which leads to the two main problems: huge dimensionality and sparse distribution in each numerical vector. In this research, documents are encoded into string
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Retracted: Automated Text Categorization

2021 3rd International Conference on Signal Processing and Communication (ICPSC), 2021
Atul Patel, Samprati Pathak, Md Irfan Khan   +2 more
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Partially Supervised Text Categorization

2009
In traditional text categorization, a classifier is built using labeled training documents from a set of predefined classes. This chapter studies a different problem: partially supervised text categorization. Given a set P of positive documents of a particular class and a set U of unlabeled documents (which contains both hidden positive and hidden ...
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Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations

Organizational Research Methods, 2022
Louis Hickman, Padmini Srinivasan
exaly