@inproceedings{StrubeMueller2022,
  author    = {Michael Strube and Mark-Christoph M{\"u}ller},
  title     = {A machine learning approach to pronoun resolution in spoken dialogue},
  series = {Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics. July 7 - 12, 2003, Sapporo, Japan},
  publisher = {Association for Computational Linguistics},
  address   = {Stroudsburg, Pennsylvania},
  doi       = {10.3115/1075096.1075118},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-111560},
  pages     = {168 -- 175},
  year      = {2022},
  abstract  = {We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NP- and non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron’s (2002) manually tuned system.},
  language  = {en}
}