Predictive Modeling: Guessing the NLP Terms of Tomorrow

Gil Francopoulo, Joseph Mariani, Patrick Paroubek

Abstract
Predictive modeling, often called “predictive analytics” in a commercial context, encompasses a variety of statistical techniques that analyze historical and present facts to make predictions about unknown events. Often the unknown events are in the future, but prediction can be applied to any type of unknown whether it be in the past or future. In our case, we present some experiments applying predictive modeling to the usage of technical terms within the NLP domain.
Anthology ID:
L16-1052
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
336–343
Language:
URL:
https://aclanthology.org/L16-1052
DOI:
Bibkey:
Cite (ACL):
Gil Francopoulo, Joseph Mariani, and Patrick Paroubek. 2016. Predictive Modeling: Guessing the NLP Terms of Tomorrow. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 336–343, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Predictive Modeling: Guessing the NLP Terms of Tomorrow (Francopoulo et al., LREC 2016)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/L16-1052.pdf
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