Knowledge Text Classification Based on Virtual Category Tree

Category Discrimination Based Feature Selection Algorithm in Chinese Text Classification

How to improve the classification precision is a major issue in the field of Chinese text classification. The tf-idf algorithm is a classic and widely-used feature selection algorithm based on VSM. But the traditional tf-idf algorithm neglects the feature term’s distribution inside category and among categories, which causes many unreasonable selective results. This paper makes an improvement t...

A Knowledge-based Approach to Text Classification

The paper presents a simple and effective knowledge-based approach for the task of text classification. The approach uses topic identification algorithm named FIFA to text classification. In this paper the basic process of text classification task and FIFA algorithm are described in detail. At last some results of experiment and evaluations are discussed.

Chinese Short Text Classification Based on Domain Knowledge

People are generating more and more short texts. There is an urgent demand to classify short texts into different domains. Due to the shortness and sparseness of short texts, conventional methods based on Vector Space Model (VSM) have limitations. To tackle the data scarcity problem, we propose a new model to directly measure the correlation between a short text instance and a domain instead of...

Correcting Category Errors in Text Classification

Multiclass Text Classification A Decision Tree based SVM Approach

This paper discusses about combining Support Vector Machine and decision trees for multi class text classification. Support Vector Machines are trained on each class at each level of the tree and the SVM which is more successful in predicting a class at that level is selected as the decision in that node. Thus a tree is constructed with different SVM in each node. And the tree constructed is us...