Results 1 - 10 of 1,689,853

A Re-Examination of Text Categorization Methods

by Yiming Yang, Xin Liu , 1999
"... This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a k-Nearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We f ..."
Abstract - Cited by 832 (24 self) - Add to MetaCart
This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a k-Nearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We

An empirical comparison of text categorization methods

by Ana Cardoso-cachopo, Arlindo Limede Oliveira, Rua Alves Redol - String Processing and Information Retrieval, 10th International Symposium , 2003
"... Abstract. In this paper we present a comprehensive comparison of the performance of a number of text categorization methods in two different data sets. In particular, we evaluate the Vector and Latent Semantic Analysis (LSA) methods, a classifier based on Support Vector Machines (SVM) and the k-Near ..."
Abstract - Cited by 17 (1 self) - Add to MetaCart
Abstract. In this paper we present a comprehensive comparison of the performance of a number of text categorization methods in two different data sets. In particular, we evaluate the Vector and Latent Semantic Analysis (LSA) methods, a classifier based on Support Vector Machines (SVM) and the k

Improving Text Categorization Methods for Event Tracking

by Yiming Yang, Tom Ault, Thomas Pierce, Charles W. Lattimer - In Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval , 2000
"... Automated tracking of events from chronologically ordered document streams is a new challenge for statistical text classification. Existing learning techniques must be adapted or improved in order to effectively handle difficult situations where the number of positive training instances per event is ..."
Abstract - Cited by 44 (5 self) - Add to MetaCart
is extremely small, the majority of training documents are unlabelled, and most of the events have a short duration in time. We adapted several supervised text categorization methods, specifically several new variants of the k-Nearest Neighbor (kNN) algorithm and a Rocchio approach, to track events. All

An application of text categorization methods to gene ontology annotation

by Kazuhiro Seki, Javed Mostafa - Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, ACM , 2005
"... This paper describes an application of IR and text categorization methods to a highly practical problem in biomedicine, specifically, Gene Ontology (GO) annotation. GO annotation is a major activity in most model organism database projects and annotates gene functions using a controlled vocabulary. ..."
Abstract - Cited by 13 (2 self) - Add to MetaCart
This paper describes an application of IR and text categorization methods to a highly practical problem in biomedicine, specifically, Gene Ontology (GO) annotation. GO annotation is a major activity in most model organism database projects and annotates gene functions using a controlled vocabulary

Abstract Improving text categorization methods for event tracking

by Yiming Yang, Tom Ault, Thomas Pierce, Charles W. Lattimer
"... Automated tracking of events from chronologically or-dered document streams is a new challenge for statis-tical text classification. Existing learning techniques must be adapted or improved in order to effectively handle difficult situations where the number of pos-itive training instances per event ..."
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event is extremely small, the majority of training documents are unlabelled, and most of the events have a short duration in time. We adapted several supervised text categorization methods, specifically several new variants of the k-Nearest Neigh-bor (kNN) algorithm and a Rocchio approach, to track

A Comparative Study on Chinese Text Categorization Methods

by Ji He, Ah-hwee Tan, Chew-Lim Tan - In Proceedings of PRICAI'2000 International Workshop on Text and Web Mining , 2000
"... This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to English text categorization, relatively few studies have been done on Chinese text categorization. Based on a People's Daily news ..."
Abstract - Cited by 14 (1 self) - Add to MetaCart
This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to English text categorization, relatively few studies have been done on Chinese text categorization. Based on a People's Daily news

MUSIC GENRES CLASSIFICATION USING TEXT CATEGORIZATION METHOD

by Kai Chen, Sheng Gao, Yongwei Zhu, Qibin Sun
"... Automatic music genre classification is one of the most challenging problems in music information retrieval and management of digital music database. In this paper, we propose a new framework using text category methods to classify music genres. This framework is different from current methods for M ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
Automatic music genre classification is one of the most challenging problems in music information retrieval and management of digital music database. In this paper, we propose a new framework using text category methods to classify music genres. This framework is different from current methods

An evaluation of statistical approaches to text categorization

by Yiming Yang - Journal of Information Retrieval , 1999
"... Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine th ..."
Abstract - Cited by 658 (22 self) - Add to MetaCart
Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine

A Centroid Based Text Categorization Method Using Mean Shift ⋆

by Man Yuan A, Yuanxin Ouyang A, Zhang Xiong A
"... Text categorization is an important research topic in Information Retrieval area and it is one of the key techniques for handling and organizing the huge amount of text data available on the Internet and other digital format in our daily life. In this paper, we propose a method for text categorizati ..."
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Text categorization is an important research topic in Information Retrieval area and it is one of the key techniques for handling and organizing the huge amount of text data available on the Internet and other digital format in our daily life. In this paper, we propose a method for text

Experiment with a hierarchical text categorization method on the WIPO-alpha

by Domonkos Tikk Department, Domonkos Tikk
"... Text categorization is the classification to assign a text document to an appropriate category in a predefined set of categories. This paper focuses on the special case when categories are organized in hierarchy. We presents a new approach on this recently emerged subfield of text categorization. Th ..."
Abstract - Cited by 8 (4 self) - Add to MetaCart
Text categorization is the classification to assign a text document to an appropriate category in a predefined set of categories. This paper focuses on the special case when categories are organized in hierarchy. We presents a new approach on this recently emerged subfield of text categorization
Results 1 - 10 of 1,689,853