- 期刊
- OpenAccess
A Dempster-Shafer Model for Feature Selection in Text Categorization
並列摘要
In this study, we propose a feature selection method based on evident theoretic model for text categorization. The proposed model is formally expressed within the Dempster-Shafer Theory of Evidence. We discuss the way the theory is used to retrieve highly informative and relevant features from the document collection. The formal retrieval function is inferred from the said model and compared our proposed model with many of the conventional feature selection methods. Experimental evaluation on standard benchmark dataset has shown the effectiveness of the proposed method.
延伸閱讀
- 洪敘峰（2008）。Using the Systematic Concept to Integrate the Decision Science Methods for Establishing Supplier Evaluation Models。資訊管理展望，10(1)，1-22。https://doi.org/10.29715/JIMCSA.200806.0001
- Huang, S. H. (2013). A novel approach for modeling driver attention allocation [doctoral dissertation, National Chiao Tung University]. Airiti Library. https://doi.org/10.6842/NCTU.2013.00377
- Chen, Z. Y., & Chen, C. C. (2015). Identifying the Stances of Topic Persons Using a Model-based Expectation-Maximization Method. Journal of Information Science and Engineering, 31(2), 573-595. https://doi.org/10.6688/JISE.2015.31.2.11
- 林樹禮（2008）。A Study of Multiple Criteria Decision Making for Integrating Dempster-Shafer Evidence theory and AHP〔碩士論文，國立屏東科技大學〕。華藝線上圖書館。https://doi.org/10.6346/NPUST.2008.00054
- Wang, H., & Fan, J. (2023). A FastText Classification Model Based on Simbert Data Augmentation. World Scientific Research Journal, 9(1), 30-41. https://doi.org/10.6911/WSRJ.202301_9(1).0004