Using Seed Words to Learn to Categorize Chinese Text

In this paper, we focus on text categorization model by unsupervised learning techniques that do not require labeled data. We propose a feature learning bootstrapping algorithm (FLB) using a small number of seed words, in that features for each of categories could be automatically learned from a lar...

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Bibliographische Detailangaben

Hauptverfasser:	Jingbo, Zhu, Wenliang, Chen, Tianshun, Yao
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Feature Case Feature Learning Information Gain Speech and sound recognition and synthesis. Linguistics Text Categorization Unlabeled Data
Online-Zugang:	Volltext
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