Comparative Study of Multilabel Classifiers on Software Engineering Q&A Community for Tag Recommendation (original) (raw)

2019

Abstract

In the paper, we are analyzing and classifying the tags of the textual content of Software Engineering, Stack Exchange Q&A website by using text pre-processing and classification algorithm. These methods were chosen because the tags provided by the dataset were too general to contextualize the questions. Further the selected classification methods are being compared using accuracy, and used to predict the tags correctly. The accuracy found for LinearSVM is the highest among all the classifiers. The tags predicted by LinearSVM has given the best results of 96% as its ROC score.

Neetu Sardana hasn't uploaded this paper.

Let Neetu know you want this paper to be uploaded.

Ask for this paper to be uploaded.