Results 11 to 20 of about 346,822 (289)

A Superior Arabic Text Categorization Deep Model (SATCDM)

IEEE Access, 2020
Categorizing Arabic text documents is considered an important research topic in the field of Natural Language Processing (NLP) and Machine Learning (ML).
M. Alhawarat, Ahmad O. Aseeri
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Noisy text categorization [PDF]

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004
This work presents categorization experiments performed over noisy texts. By noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g., transcriptions of speech recordings extracted with a recognition system).
openaire   +2 more sources

Using bag-of-concepts to improve the performance of support vector machines in text categorization [PDF]

, 2004
This paper investigates the use of concept-based representations for text categorization. We introduce a new approach to create concept-based text representations, and apply it to a standard text categorization collection. The representations are used as
Cöster, Rickard, Sahlgren, Magnus
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Categorization and Conceptualization of Space in Descriptive Text

Научный диалог, 2020
The relevance of the article is due to the importance of studying spatial semantics in the new scientific paradigm. The possibility of studying genre varieties of description (description-landscape, description-interior, description-portrait, description
Y. N. Varfolomeeva
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An efficient approach for textual data classification using deep learning

Frontiers in Computational Neuroscience, 2022
Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data.
Abdullah Alqahtani, Habib Ullah Khan, Shtwai Alsubai, Mohemmed Sha, Ahmad Almadhor, Tayyab Iqbal, Sidra Abbas   +6 more
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Machine Learning in Automated Text Categorization [PDF]

, 2001
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them.
ANDROUTSOPOULOS I., ATTARDI G., BAKER L.D., BIEBRICHER P., CAROPRESO M.F., CAVNAR W.B., CHAKRABARTI S., CLACK C., CLEVERDON C., COHEN W. W., COHEN W. W., COHEN W.W., DAGAN I., DEERWESTER S., DENOYER L., DIAZ ESTEBAN A., DRUCKER H., DUMAIS S.T., DUMAIS S.T., ESCUDERO G., Fabrizio Sebastiani, FIELD B., FORSYTH R. S., FUHR N., FUHR N., FUHR N., FURNKRANZ J., GALAVOTTI L., GALE W. A., GOVERT N., GRAY W.A., GUTHRIE L., HAYES P.J., HEAPS H., HERSH W., HULL D. A., HULL D. A., ITTNER D.J., IWAYAMA M., IYER R.D., JOACHIMS T., JOACHIMS T., JOACHIMS T., JOHN G. H., JUNKER M., JUNKER M., KESSLER B., KIM Y.-H., KLINKENBERG R., KNORZ G., KOLLER D., LAM S.L., LAM W., LAM W., LANG K., LARKEY L. S., LARKEY L. S., LARKEY L.S., LEWIS D. D., LEWIS D. D., LEWIS D. D., LEWIS D. D., LEWIS D.D., LEWIS D.D., LEWIS D.D., LEWIS D.D., LEWIS D.D., LI H., LI Y.H., LIERE R., LIM J. H., MASAND B., MASAND B., MCCALLUM A. K., MCCALLUM A.K., MLADENIC D., MLADENIC D., MOULINIER I., MOULINIER I., MYERS K., NG H.T., OH H.-J., PAZIENZA M. T., RILOFF E., ROBERTSON S.E., ROBERTSON S.E., ROTH D., RUIZ M.E., SABLE C.L., SARACEVIC T., SCHAPIRE R. E., SCHUTZE H., SCHUTZE H., SCOTT S., SEBASTIANI F., SINGHAL A., SLONIM N., TAIRA H., TUMER K., TZERAS K., VAN RIJSBERGEN C. J., WIENER E.D., YANG Y., YANG Y., YANG Y., YANG Y., YU K.L.   +106 more
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Cross-Lingual Text Categorization [PDF]

, 2003
This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when documents in different languages must be classified according to the same classification tree. We describe practical and cost-effective solutions for automatic Cross-Lingual Text Categorization, both in case a sufficient number of training examples is ...
Bel Rafecas, Núria, Koster, C. H. A., Villegas, Marta   +2 more
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Parallel noise eliminate: A parallel noise elimination algorithm for massive text categorization

Journal of Algorithms & Computational Technology, 2018
Noise data in text are one of the main factors affecting the quality of text categorization. A parallel noise data elimination algorithm based on principal component analysis method and term frequency-inverse document frequency method for the noise data ...
Xiaojuan Hu, Lei Liu, Ningjia Qiu, Meng Li   +3 more
doaj   +1 more source

Fragments and text categorization [PDF]

Proceedings of the ACL 2004 on Interactive poster and demonstration sessions -, 2004
We introduce two novel methods of text categorization in which documents are split into fragments. We conducted experiments on English, French and Czech. In all cases, the problems referred to a binary document classification. We find that both methods increase the accuracy of text categorization.
Jan Blaták, Eva Mráková, Luboš Popelínský   +2 more
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Adaptive text mining: Inferring structure from sequences [PDF]

, 2004
Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes.
Witten, Ian H.
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