An efficient feature selection method using named entity recognition for Chinese text categorization
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- Type
- article
- Published
- 2009-07-12
- Cited by
- 3
- References
- 12
- OpenAlex
- https://openalex.org/W2045780747
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8060482
Keywords
Feature selection, Computer science, Text categorization, Weighting, Artificial intelligence
References
- Beyond TFIDF Weighting for Text Categorization in the Vector Space Model
- Chinese Named Entity Recognition with Conditional Random Fields
- A Maximum Entropy Approach to Named Entity Recognition
- Efficient Support Vector Classifiers for Named Entity Recognition
- Using ambiguity measure feature selection algorithm for support vector machine classifier
- Chinese Segmentation and New Word Detection using Conditional Random Fields
- Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging
- Named Entity Recognition using an HMM-based Chunk Tagger
- Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
- A novel refinement approach for text categorization
- A comprehensive comparative study on term weighting schemes for text categorization with support vector machines
- A Comparative Study on Feature Selection in Text Categorization
Cited by
- Effect of Named Entities in Web Page Classification
- Contribution to automatic text classification: metrics and evolutionary algorithms. (Contributions à la classification automatique de texte: métriques et algorithmes évolutifs)
- Hierarchical Text Classification for News Articles Based-on Named Entities
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