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arXiv · 1911.12224

Multi-label Classification for Automatic Tag Prediction in the Context of Programming Challenges

Bianca Iancu·Gabriele Mazzola·Kyriakos Psarakis·Panagiotis Soilis
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Abstract

One of the best ways for developers to test and improve their skills in a fun and challenging way are programming challenges, offered by a plethora of websites. For the inexperienced ones, some of the problems might appear too challenging, requiring some suggestions to implement a solution. On the other hand, tagging problems can be a tedious task for problem creators. In this paper, we focus on automating the task of tagging a programming challenge description using machine and deep learning methods. We observe that the deep learning methods implemented outperform well-known IR approaches such as tf-idf, thus providing a starting point for further research on the task.

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BibTeXRIS

Bianca Iancu, Gabriele Mazzola, Kyriakos Psarakis, Panagiotis Soilis. 2019-11-27. Multi-label Classification for Automatic Tag Prediction in the Context of Programming Challenges. https://arxiv.org/abs/1911.12224

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