A tag2Vec approach for questions tag suggestion on community question answering sites

Abstract

There are several reasons behind a question do not receive an answer. One of them is user do not provide the proper keyword called Tag to their question that summarizes their question domain and topic. Tag plays an important role in questions asked by the users in Community Question Answering (CQA) sites. They are used for grouping questions and finding relevant answerers in these sites. Users of these sites can select a tag from the existing tag list or contribute a new tag to their questions. The process of tagging is manual, which results in inconsistent and sometimes even incorrect or incomplete tagging. To overcome this issue, we design an automatic tag suggestion technique which can suggest tags to the users based on their question text. It serves to minimize the error of the manual tagging system by providing more relevant tags to questions. The performance of the proposed system is evaluated using Precision, Recall, and F1-score.