首页> 外文期刊>International Journal of Information Engineering and Electronic Business >An Improved Information Retrieval Approach to Short Text Classification
【24h】

An Improved Information Retrieval Approach to Short Text Classification

机译:一种改进的短文本分类信息检索方法

获取原文
           

摘要

Twitter act as a most important medium of communication and information sharing. As tweets do not provide sufficient word occurrences i.e. of 140 characters limits, classification methods that use traditional approaches like “Bag-Of-Words” have limitations. The proposed system used an intuitive approach to determine the class labels with the set of features. The System can able to classify incoming tweets mainly into three generic categories: News, Movies and Sports. Since these categories are diverse and cover most of the topics that people usually tweet about .Experimental results using the proposed technique outperform the existing models in terms of accuracy.
机译:Twitter是沟通和信息共享的最重要媒介。由于推文无法提供足够的单词出现,即不能超过140个字符,因此使用传统方法(例如“单词袋”)的分类方法会受到限制。所提出的系统使用一种直观的方法来确定具有特征集的类别标签。系统可以将传入的推文主要分为三类:新闻,电影和体育。由于这些类别是多种多样的,并且涵盖了人们通常会发布的大多数主题。使用本文提出的技术获得的实验结果在准确性方面优于现有模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号