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Inproceedings3733

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TECNE: Knowledge Based Text Classification Using Network Embeddings




Published: 2018 Dezember

Buchtitel: Proc. 21st International Conference on Knowledge Engineering and Knowledge Management 2018 (EKAW 2018)
Nummer: 2262
Seiten: 53-56
Verlag: CEUR Workshop Proceedings

Referierte Veröffentlichung

BibTeX

Kurzfassung
Text classification is an important and challenging task due news filtering. Several supervised learning approaches have been proposed for text classification. However, most of them require a significant amount of training data. Manually labeling such data can be very time-consuming and costly. To overcome the problem of labeled data, we demonstrate TECNE, a knowledge-based text classification method using network embeddings. The proposed system does not require any labeled training data to classify an arbitrary text. Instead, it relies on a set of predefined categories to determine a category which the given document belongs to.

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Forschungsgruppe

Information Service Engineering


Forschungsgebiet