@InProceedings{cheng-EtAl:2018:C18-2,
  author    = {Cheng, Shang-Chien  and  Chen, Jhih-Jie  and  Yang, Chingyu  and  Chang, Jason},
  title     = {LanguageNet: Learning to Find Sense Relevant Example Sentences},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico},
  publisher = {Association for Computational Linguistics},
  pages     = {99--102},
  abstract  = {In this paper, we present a system, LanguageNet, which can help second language learners to search for different meanings and usages of a word. We disambiguate word senses based on the pairs of an English word and its corresponding Chinese translations in a parallel corpus, UM-Corpus. The process involved performing word alignment, learning vector space representations of words and training a classifier to distinguish words into groups of senses. LanguageNet directly shows the definition of a sense, bilingual synonyms and sense relevant examples.},
  url       = {http://www.aclweb.org/anthology/C18-2022}
}