@inproceedings{Wartena2013,
  author    = {Christian Wartena},
  title     = {HsH: Estimating Semantic Similarity of Words and Short Phrases with Frequency Normalized Distance Measures},
  series = {Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)},
  editor    = {Suresh Manandhar and Deniz Yuret},
  publisher = {Association for Computational Linguistics},
  doi       = {10.25968/opus-2077},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus4-20778},
  pages     = {48 -- 52},
  year      = {2013},
  abstract  = {This paper describes the approach of the Hochschule Hannover to the SemEval 2013 Task Evaluating Phrasal Semantics. In order to compare a single word with a two word phrase we compute various distributional similarities, among which a new similarity measure, based on Jensen-Shannon Divergence with a correction for frequency effects. The classification is done by a support vector machine that uses all similarities as features. The approach turned out to be the most successful one in the task.},
  language  = {en}
}