Hierarchical Text Classification corpora

<p>A set of 3 datasets for Hierarchical Text Classification (HTC), with samples divided into training and testing splits. The hierarchies of labels within all datasets have depth 2.</p> <ul> <li>The <strong>Amazon5x5</strong> dataset contains 500,000 user reviews tagged with the reviewed product's categories. There are 5 product categories with 100,000 examples each, and each category has 5 sub-categories.</li> <li>The <strong>Bugs</strong> dataset contains 30,050 bugs of the Linux kernel, labeled with exactly two categories identifying the affected component.</li> <li>Finally, the <strong>Web Of Science</strong> dataset contains 46,960 abstracts of scientific papers, labeled the article's domain (see <a href="https://data.mendeley.com/datasets/9rw3vkcfy4/6">original repo</a> for more details).</li> </ul> <p>Datasets are published in JSONL format, where each line is a string formatted as a JSON, like in the example below.</p> <pre><code>{ "text": &lt;article text&gt;, "labels": [&lt;label1&gt;, &lt;label2&gt;, ...] }</code></pre> <p>The <em>hierarchical structure</em> of labels in each dataset is documented in <a href="https://gitlab.com/distration/dsi-nlp-publib/-/tree/main/htc-survey-24/data/taxonomies">this repository</a>.</p> <p>&nbsp;</p> <p>These datasets have been presented in this paper:</p> <ul> <li>"Hierarchical Text Classification and its Foundations: a Review of Current Research" - DOI: <a href="https://doi.org/10.3390/electronics13071199">10.3390/electronics13071199</a></li> </ul> <p>Some of these datasets have also been used in:</p> <ul> <li>"Ticket Automation: an Insight into Current Research with Applications to Multi-level Classification Scenarios" - DOI: <a href="https://doi.org/10.1016/j.eswa.2023.119984">10.1016/j.eswa.2023.119984</a></li> <li>"A multi-level approach for hierarchical Ticket Classification", accepted at WNUT 2022 - <a href="https://aclanthology.org/2022.wnut-1.22/">link</a></li> </ul> <p>&nbsp;</p> <p>These datasets are partially derived from previous work, namely:</p> <ul> <li>[Amazon] J. Ni, J. Li, J. McAuley, "Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects", EMNLP 2019, doi: <a href="http://dx.doi.org/10.18653/v1/D19-1018">10.18653/v1/D19-1018</a></li> <li>[WOS] K. Kowsari, D. E. Brown, M. Heidarysafa, K. Jafari Meimandi, M. S. Gerber and L. E. Barnes, "HDLTex: Hierarchical Deep Learning for Text Classification," 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), 2017, pp. 364-371, doi: <a href="http://doi.org/10.1109/ICMLA.2017.0-134">10.1109/ICMLA.2017.0-134</a></li> <li>[Linux Bugs] V. Lyubinets, T. Boiko and D. Nicholas, "Automated Labeling of Bugs and Tickets Using Attention-Based Mechanisms in Recurrent Neural Networks," <em>2018 IEEE Second International Conference on Data Stream Mining &amp; Processing (DSMP)</em>, 2018, pp. 271-275, doi: <a href="http://doi.org/10.1109/DSMP.2018.8478511">10.1109/DSMP.2018.8478511</a></li> </ul>