@InProceedings{balachandran-EtAl:2018:W-NUT2018,
  author    = {Balachandran, Vidhisha  and  Rajagopal, Dheeraj  and  Kanjirathinkal, Rose Catherine  and  Cohen, William},
  title     = {Learning to Define Terms in the Software Domain},
  booktitle = {Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {164--172},
  abstract  = {One way to test a person's knowledge of a domain is to ask them to define domain-specific terms. Here, we investigate the task of automatically generating definitions of technical terms by reading text from the technical domain. Specifically, we learn definitions of software entities from a large corpus built from the user forum Stack Overflow. To model definitions, we train a language model and incorporate additional domain-specific information like word-word co-occurrence, and ontological category information. Our approach improves previous baselines by 2 BLEU points for the definition generation task. Our experiments also show the additional challenges associated with the task and the short-comings of language-model based architectures for definition generation.},
  url       = {http://www.aclweb.org/anthology/W18-6122}
}