Evaluating measures of semantic relatedness for Russian language

7 pages•Published: March 18, 2019

Abstract

Coreference resolution is recognized as an important task in natural text processing and it has been proven that knowledge of semantic relations between two possibly coreferent entities can provide a certain increase in quality for automated solutions. One of the ways to integrate semantic information in such a system is to measure semantic relatedness between candidates for establishing coreference relation. This research is devoted to evaluating the efficiency of different types of semantic relatedness metrics, calculated from different sources, for coreference resolution on the material of Russian language.

Keyphrases: information extraction, natural language processing, semantic relatedness, wikipedia mining

In: Gerhard Wohlgenannt, Ruprecht von Waldenfels, Svetlana Toldova, Ekaterina Rakhilina, Denis Paperno, Olga Lyashevskaya, Natalia Loukachevitch, Sergei O. Kuznetsov, Olga Kultepina, Dmitry Ilvovsky, Boris Galitsky, Ekaterina Artemova and Elena Bolshakova (editors). Proceedings of Third Workshop "Computational linguistics and language science", vol 4, pages 26-32.

Links:	https://easychair.org/publications/paper/65k7
	https://doi.org/10.29007/4qcp

BibTeX entry

@inproceedings{CLLS2018:Evaluating_measures_semantic_relatedness,
  author    = {Ilya Azerkovich},
  title     = {Evaluating measures of semantic relatedness for Russian language},
  booktitle = {Proceedings of Third Workshop "Computational linguistics and language science"},
  editor    = {Gerhard Wohlgenannt and Ruprecht von Waldenfels and Svetlana Toldova and Ekaterina Rakhilina and Denis Paperno and Olga Lyashevskaya and Natalia Loukachevitch and Sergei O. Kuznetsov and Olga Kultepina and Dmitry Ilvovsky and Boris Galitsky and Ekaterina Artemova and Elena Bolshakova},
  series    = {EPiC Series in Language and Linguistics},
  volume    = {4},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5283},
  url       = {/publications/paper/65k7},
  doi       = {10.29007/4qcp},
  pages     = {26-32},
  year      = {2019}}

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