A Method for Chinese Short Text Classification Considering Effective Feature Expansion

Abstract

 This paper presents a Chinese short text classification method which considering extended semantic constraints and statistical constraints. This method uses “HowNet” tools to build the attribute set of concept. when coming to the part of feature expansion, we judge the collocation between the attribute words of original text and the characteristics before and after expansion as the semantic constraints, and calculate the ratio between the mutual information of the original contents and the features before expansion versus the mutual information of the original contents and the features after expansion as statistical constraints, so as to judge whether feature expansion is effective with this two constraints , then rationally use various semantic relation word-pairs in short text classification. Experiments show that this method can use semantic relations in Chinese short text classification effectively, and improve the classification performance.

Authors and Affiliations

Mingxuan liu , Xinghua Fan

Keywords

Related Articles

An Efficient Routing Protocol under Noisy Environment for Mobile Ad Hoc Networks using Fuzzy Logic

A MANET is a collection of mobile nodes communicating and cooperating with each other to route a packet from the source to their destinations. A MANET is used to support dynamic routing strategies in absence of wired inf...

 Iris Compression and Recognition using Spherical Geometry Image

 this research is considered to be a research to attract attention to the 3D iris compression to store the database of the iris. Actually, the 3D iris database cannot be found and in trying to solve this problem 2D...

 An Inference Mechanism Framework for Association Rule Mining

 Available approaches for Association Rule Mining (ARM) generates a large number of association rules, these rules may be trivial and redundant and also such rules are difficult to manage and understand for the user...

 Density Based Support Vector Machines for Classification

 Support Vector Machines (SVM) is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification) of training points. However, sometimes there...

 Prediction of Employee Turnover in Organizations using Machine Learning Algorithms

 Employee turnover has been identified as a key issue for organizations because of its adverse impact on work place productivity and long term growth strategies. To solve this problem, organizations use machine lear...

Download PDF file
  • EP ID EP130001
  • DOI -
  • Views 88
  • Downloads 0

How To Cite

Mingxuan liu, Xinghua Fan (2012).  A Method for Chinese Short Text Classification Considering Effective Feature Expansion. International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(1), 1-5. https://europub.co.uk/articles/-A-130001