返回
Survey on supervised machine learning techniques for automatic text classification
DOI:10.1007/s10462-018-09677-1.png)
摘要
En 中文
Supervised machine learning studies are gaining more significant recently because of the availability of the increasing number of the electronic documents from different resources. Text classification can be defined that the task was automatically categorized a group documents into one or more predefined classes according to their subjects. Thereby, the major objective of text classification is to enable users for extracting information from textual resource and deals with process such as retrieval, classification, and machine learning techniques together in order to classify different pattern. In text classification technique, term weighting methods design suitable weights to the specific terms to enhance the text classification performance. This paper surveys of text classification, process of different term weighing methods and comparison between different classification techniques.
Keyword:
Supervised machine learning
Text classification
Term weighting
Classification techniques
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.9
论文数:
6.1K
被引数:
1.9W
机构
引用论文
Sequence Comparison of the EcoHK31I and EaeI. Restriction-Modification Systems Suggests an Intergenic Transfer of Genetic Material
bchm
IF0

