TY - GEN
T1 - Skip N-grams and ranking functions for predicting script events
AU - Jans, Bram
AU - Bethard, Steven
AU - Vulíc, Ivan
AU - Moens, Marie Francine
N1 - Publisher Copyright:
© 2012 Association for Computational Linguistics.
PY - 2012
Y1 - 2012
N2 - In this paper, we extend current state-of-Theart research on unsupervised acquisition of scripts, that is, stereotypical and frequently observed sequences of events. We design, evaluate and compare different methods for constructing models for script event prediction: given a partial chain of events in a script, predict other events that are likely to belong to the script. Our work aims to answer key questions about how best to (1) identify representative event chains from a source text, (2) gather statistics from the event chains, and (3) choose ranking functions for predicting new script events. We make several contributions, introducing skip-grams for collecting event statistics, designing improved methods for ranking event predictions, defining a more reliable evaluation metric for measuring predictiveness, and providing a systematic analysis of the various event prediction models.
AB - In this paper, we extend current state-of-Theart research on unsupervised acquisition of scripts, that is, stereotypical and frequently observed sequences of events. We design, evaluate and compare different methods for constructing models for script event prediction: given a partial chain of events in a script, predict other events that are likely to belong to the script. Our work aims to answer key questions about how best to (1) identify representative event chains from a source text, (2) gather statistics from the event chains, and (3) choose ranking functions for predicting new script events. We make several contributions, introducing skip-grams for collecting event statistics, designing improved methods for ranking event predictions, defining a more reliable evaluation metric for measuring predictiveness, and providing a systematic analysis of the various event prediction models.
UR - http://www.scopus.com/inward/record.url?scp=84986217572&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84986217572&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84986217572
T3 - EACL 2012 - 13th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings
SP - 336
EP - 344
BT - EACL 2012 - 13th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings
PB - Association for Computational Linguistics (ACL)
T2 - 13th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2012
Y2 - 23 April 2012 through 27 April 2012
ER -