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Text categorization: past and present
Artificial Intelligence Review, 2020Automatic text categorization is the operation of sorting out the text documents into pre-defined text categories using some machine learning algorithms. Normally, it defines the most important approaches to organizing and making the use of a large volume of information exists in unstructured form.
Ankita Dhar +2 more
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Text categorization for streams
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007We describe a novel system for evaluating and performing stream-based text categorization. Stream-based text categorization considers the text being categorized as a stream of symbols, which differs from the traditional feature-based approach which relies on extracting features from the text.
D. L. Thomas, W. J. Teahan
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An algorithm for text categorization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, 2008A novel and efficient learning algorithm is proposed for the binary linear classification problem. The algorithm is trained using the Rocchio's relevance feedback technique and builds a classifier by the intermediate hyperplane of two common tangent hyperplanes for the given category and its complement.
Anestis Gkanogiannis +1 more
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, 2005 During the last 15 years, the production of documents in digital form has exploded, due to the increased availability of hardware and software tools for generating digital data (e.g., personal computers, digital cameras, word processors) and for digitizing data that had been originated in nondigital form (e.g., scanners, OCR software).
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2003
The sudden expansion of the web and the use of the internet has caused some research fields to regain (or even increase) its old popularity. Of them, text categorization aims at developing a classification system for assigning a number of predefined topic codes to the documents based on the knowledge accumulated in the training process.
Hayri Sever +2 more
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The sudden expansion of the web and the use of the internet has caused some research fields to regain (or even increase) its old popularity. Of them, text categorization aims at developing a classification system for assigning a number of predefined topic codes to the documents based on the knowledge accumulated in the training process.
Hayri Sever +2 more
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Exploiting Hierarchy in Text Categorization
Information Retrieval, 1999With 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 +2 more
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2009
Text categorization (TC) is a data mining technique for automatically classifying documents to one or more predefined categories. This paper will introduce the principles of TC, discuss common TC methods and steps, give an overview of the various types of TC systems, and discuss future trends. TC systems begin with a group of known categories and a set
Megan Chenoweth, Min Song
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Text categorization (TC) is a data mining technique for automatically classifying documents to one or more predefined categories. This paper will introduce the principles of TC, discuss common TC methods and steps, give an overview of the various types of TC systems, and discuss future trends. TC systems begin with a group of known categories and a set
Megan Chenoweth, Min Song
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Deep encrypted text categorization
2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017Long short-term memory (LSTM) is a significant approach to capture the long-range temporal context in sequences of arbitrary length. This had shown astonishing performance in sentence and document modeling. To leverage this, we use LSTM network to the encrypted text categorization at character and word level of texts.
R. Vinayakumar +2 more
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