Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции
Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects. / Mitrofanova, O.; Lashevskaya, Olga; Panicheva, Polina.
Text, Speech and Dialogue : Proceedings of the 11th International Conference TSD 2008, Brno, Czech Republic, September 8–12, 2008. Springer Nature, 2008. стр. 153-159 (Lecture Notes in Computer Science; Том 5246).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции
}
TY - GEN
T1 - Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects
AU - Mitrofanova, O.
AU - Lashevskaya, Olga
AU - Panicheva, Polina
N1 - Mitrofanova, O., Lashevskaya, O., Panicheva, P. (2008). Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_21
PY - 2008
Y1 - 2008
N2 - The paper presents experimental results on automatic word sense disambiguation (WSD). Contexts for polysemous and/or homonymic Russian nouns denoting physical objects serve as an empirical basis of the study. Sets of contexts were extracted from the Russian National Corpus (RNC). Machine learning software for WSD was developed within the framework of the project. WSD tool used in experiments is aimed at statistical processing and classification of noun contexts. WSD procedure was performed taking into account lexical markers of word meanings in contexts and semantic annotation of contexts. Sets of experiments allowed to define optimal conditions for WSD in Russian texts.
AB - The paper presents experimental results on automatic word sense disambiguation (WSD). Contexts for polysemous and/or homonymic Russian nouns denoting physical objects serve as an empirical basis of the study. Sets of contexts were extracted from the Russian National Corpus (RNC). Machine learning software for WSD was developed within the framework of the project. WSD tool used in experiments is aimed at statistical processing and classification of noun contexts. WSD procedure was performed taking into account lexical markers of word meanings in contexts and semantic annotation of contexts. Sets of experiments allowed to define optimal conditions for WSD in Russian texts.
M3 - Conference contribution
SN - 978-3-540-873-90-7
T3 - Lecture Notes in Computer Science
SP - 153
EP - 159
BT - Text, Speech and Dialogue
PB - Springer Nature
T2 - Text, Speech and Dialogue
Y2 - 8 September 2008 through 12 September 2008
ER -
ID: 4509713