Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Comparative Evaluation and Integration of Collocation Extraction Metrics. / Zakharov, Victor .
Text, Speech, and Dialogue: 20th International Conference, TSD 2017, Prague, Czech Republic, August 27-31, 2017, Proceedings. Cham : Springer Nature, 2017. p. 255-262 (Lecture Notes in Computer Science; Vol. 10415).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Comparative Evaluation and Integration of Collocation Extraction Metrics
AU - Zakharov, Victor
N1 - Zakharov V. (2017) Comparative Evaluation and Integration of Collocation Extraction Metrics. In: Ekštein K., Matoušek V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science, vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_29
PY - 2017
Y1 - 2017
N2 - The paper deals with collocation extraction from corpus data. A whole number of formulae have been created to integrate different factors that determine the association between the collocation components. The experiments are described which objective was to study the method of collocation extraction based on the statistical association measures. The work is focused on bigram collocations. The obtained data on the measure precision allow to establish to some degree that some measures are more precise than others. No measure is ideal, which is why various options of their integration are desirable and useful. We propose a number of parameters that allow to rank collocates in an combined list, namely, an average rank, a normalized rank and an optimized rank.
AB - The paper deals with collocation extraction from corpus data. A whole number of formulae have been created to integrate different factors that determine the association between the collocation components. The experiments are described which objective was to study the method of collocation extraction based on the statistical association measures. The work is focused on bigram collocations. The obtained data on the measure precision allow to establish to some degree that some measures are more precise than others. No measure is ideal, which is why various options of their integration are desirable and useful. We propose a number of parameters that allow to rank collocates in an combined list, namely, an average rank, a normalized rank and an optimized rank.
KW - Collocation extraction
KW - Association measures
KW - Evaluation ‧ Ranking
KW - Average rank ‧
KW - Normalized rank ‧
KW - Optimized rank
KW - Collocation extraction
KW - Association measures
KW - Evaluation
KW - Ranking
KW - Average rank
KW - Normalized rank
KW - Optimized rank
UR - https://link.springer.com/chapter/10.1007/978-3-319-64206-2_29
M3 - Conference contribution
SN - 978-3-319-64205-5
T3 - Lecture Notes in Computer Science
SP - 255
EP - 262
BT - Text, Speech, and Dialogue
PB - Springer Nature
CY - Cham
T2 - Text, Speech, and Dialogue
Y2 - 27 August 2017 through 31 August 2017
ER -
ID: 71300483