원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.7 No.1
2014.02
pp.61-70
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set. If a document belongs to exactly one of the categories, it is a single-label classification task; otherwise, it is a multi-label classification task. TC uses several tools from Information Retrieval (IR) and Machine Learning (ML) and has received much attention in the last years from both researchers in the academia and industry developers. In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents.
목차
Abstract
1. Introduction
2. Classification Methods
2.1. Naive Bayes
2.2. Term Graph Model
2.3. k-Nearest Neighbors
3. Experimental Results
3.1. Dataset
3.2. Implementation
3.3. Results
4. Conclusion
References
1. Introduction
2. Classification Methods
2.1. Naive Bayes
2.2. Term Graph Model
2.3. k-Nearest Neighbors
3. Experimental Results
3.1. Dataset
3.2. Implementation
3.3. Results
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보