Relational Text Classification Algorithm Based on iTopicModel
Liming Wang · 2011
In order to solve the problem that traditional text classification methods do not emphasize the links among text documents enough,this paper proposes a novel text classification algorithm TC-iTM based on iTopicModel.TC-iTM uses the probability that the labeled documents are assigned to each topic to judge the category that each topic represents.TC-iTM classifies unlabelled documents by using the probability that the documents are assigned to each topic and the text information of these documents.Experimental result shows that TC-iTM outperforms the traditional text classification methods when links among documents are important to the categories of the documents in document network.