Results 221 to 230 of about 1,767,419 (268)

One size fits all: Enhanced zero-shot text classification for patient listening on social media. [PDF]

Front Artif Intell
Matoshi V, De Vuono MC, Gaspari R, Kröll M, Jantscher M, Nicolardi SL, Mazzola G, Rauch M, Sabol V, Salhofer E, Mariani R.   +10 more
europepmc   +1 more source

Research of multi-label text classification based on label attention and correlation networks. [PDF]

PLoS One
Yuan L, Xu X, Sun P, Yu HP, Wei YZ, Zhou JJ.   +5 more
europepmc   +1 more source

From outputs to insights: a survey of rationalization approaches for explainable text classification. [PDF]

Front Artif Intell
Mendez Guzman E, Schlegel V, Batista-Navarro R.   +2 more
europepmc   +1 more source

Chinese text classification method based on sentence information enhancement and feature fusion. [PDF]

Heliyon
Zhu B, Pan W.
europepmc   +1 more source

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The impact of preprocessing on text classification

Information Processing and Management, 2014
Preprocessing is one of the key components in a typical text classification framework. This paper aims to extensively examine the impact of preprocessing on text classification in terms of various aspects such as classification accuracy, text domain, text language, and dimension reduction.
Alper Kursat Uysal, Serkan Günal
exaly   +3 more sources

Classification of text documents

Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 1998
Summary: 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.
Yonghong Li, Anil K. Jain 0001
openaire   +2 more sources

Urdu text classification

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
openaire   +1 more source

Concatenate text embeddings for text classification

2017 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC), 2017
Text embedding has gained a lot of interests in text classification area. This paper investigates the popular neural document embedding method Paragraph Vector as a source of evidence in document ranking. We focus on the effects of combining knowledge-based with knowledge-free document embeddings for text classification task.
Hamid Machhour, Ismail Kassou
openaire   +1 more source

Text Generation for Imbalanced Text Classification

2019 16th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2019
The problem of imbalanced data can be frequently found in the real-world data. It leads to the bias of classification models, that is, the models predict most samples as major classes which are often the negative class. In this research, text generation techniques were used to generate synthetic minority class samples to make the text dataset balanced.
Suphamongkol Akkaradamrongrat, Pornpimon Kachamas, Sukree Sinthupinyo   +2 more
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Bilingual Text Classification

2007
Bilingual documentation has become a common phenomenon in official institutions and private companies. In this scenario, the categorization of bilingual text is a useful tool. In this paper, different approaches will be proposed to tackle this bilingual classification task.
Jorge Civera, Elsa Cubel, Enrique Vidal 0001   +2 more
openaire   +1 more source