Results 121 to 130 of about 1,750,419 (157)
Chinese text classification method based on sentence information enhancement and feature fusion. [PDF]
HeliyonZhu B, Pan W.
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HGATT_LR: transforming review text classification with hypergraphs attention layer and logistic regression. [PDF]
Sci RepPradeepa S +6 more
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Deep learning uncertainty quantification for clinical text classification. [PDF]
J Biomed InformPeluso A +16 more
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A text classification method by integrating mobile inverted residual bottleneck convolution networks and capsule networks with adaptive feature channels. [PDF]
Sci RepJin T, Liu J.
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Joint coordinate attention mechanism and instance normalization for COVID online comments text classification. [PDF]
PeerJ Comput SciZhu R, Gao HH, Wang Y.
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2017
In this chapter, a supervised automatic text documents classification using the fuzzy decision trees technique is proposed. Whatever the algorithm used in the fuzzy decision trees, there must be a criterion for the choice of discriminating attribute at the nodes to partition.
Ben Elfadhl Mohamed Ahmed +1 more
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In this chapter, a supervised automatic text documents classification using the fuzzy decision trees technique is proposed. Whatever the algorithm used in the fuzzy decision trees, there must be a criterion for the choice of discriminating attribute at the nodes to partition.
Ben Elfadhl Mohamed Ahmed +1 more
openaire +2 more sources
Classification of Text Documents
The Computer Journal, 1998Summary: The exponential growth of the internet has led to a great deal of interest in developing useful and efficient tools and software to assist users in searching the Web. Document retrieval, categorization, routing and filtering can all be formulated as classification problems.
Li, Y. H., Jain, A. K.
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Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
Recently, dataless text classification has attracted increasing attention. It trains a classifier using seed words of categories, rather than labeled documents that are expensive to obtain. However, a small set of seed words may provide very limited and noisy supervision information, because many documents contain no seed words or only irrelevant seed ...
Ximing Li +4 more
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Recently, dataless text classification has attracted increasing attention. It trains a classifier using seed words of categories, rather than labeled documents that are expensive to obtain. However, a small set of seed words may provide very limited and noisy supervision information, because many documents contain no seed words or only irrelevant seed ...
Ximing Li +4 more
openaire +1 more source
2020
The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of ...
Sreyan Ghosh +3 more
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The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of ...
Sreyan Ghosh +3 more
openaire +1 more source
Proceedings of the 7th International Conference on Frontiers of Information Technology, 2009
This paper compares statistical techniques for text classification using Naive Bayes and Support Vector Machines, in context of Urdu language. A large corpus is used for training and testing purpose of the classifiers. However, those classifiers cannot directly interpret the raw dataset, so language specific preprocessing techniques are applied on it ...
Abbas Raza Ali, Maliha Ijaz
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This paper compares statistical techniques for text classification using Naive Bayes and Support Vector Machines, in context of Urdu language. A large corpus is used for training and testing purpose of the classifiers. However, those classifiers cannot directly interpret the raw dataset, so language specific preprocessing techniques are applied on it ...
Abbas Raza Ali, Maliha Ijaz
openaire +1 more source