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31,944
A Re-Examination of Text Categorization Methods
, 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
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Cited by 853 (24 self)
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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
- 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 ..."
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Cited by 20 (1 self)
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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
- 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 ..."
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Cited by 46 (5 self)
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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
- 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. ..."
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Cited by 13 (2 self)
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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
"... 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
- 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 ..."
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Cited by 16 (1 self)
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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
"... 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 ..."
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Cited by 3 (0 self)
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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
- 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 ..."
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Cited by 663 (22 self)
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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
Experiment with a hierarchical text categorization method on the WIPO-alpha
"... 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 ..."
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Cited by 8 (4 self)
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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
A Comparison of TextCategorization Methods Applied to NGram Frequency Statistics
- In Australian Joint Conference on Artificial Intelligence
, 2004
"... Abstract. This paper gives an analysis of multi-class e-mail categoriza-tion performance, comparing a character n-gram document representa-tion against a word-frequency based representation. Furthermore the im-pact of using available e-mail specific meta-information on classification performance is ..."
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Cited by 9 (1 self)
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Abstract. This paper gives an analysis of multi-class e-mail categoriza-tion performance, comparing a character n-gram document representa-tion against a word-frequency based representation. Furthermore the im-pact of using available e-mail specific meta-information on classification performance
Results 1 - 10
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31,944
