Multi-label Hierarchical Text Classification using the ACM Taxonomy

Abstract

Many of the works of text classification involve the attribution of each text a single class label from a predefined set of classes, usually small and flat organized (flat classification). However, there are more complex classification problems in which we can assign to each text more than one class (multi-label classification), that can be organized in a hierarchical structure (hierarchical classification) to support thematic searches by browsing topics of interests. In this paper, a problem of multi-label hierarchical text classification is presented. The experiment involves the creation of a multi-label hierarchical text collection, its pre-processing, followed by the application of different classifiers to the collection, and finally, the evaluation of the classifiers performance.