@inproceedings{francopoulo-etal-2016-predictive,
title = "Predictive Modeling: Guessing the {NLP} Terms of Tomorrow",
author = "Francopoulo, Gil and
Mariani, Joseph and
Paroubek, Patrick",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}`16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1052/",
pages = "336--343",
abstract = "Predictive modeling, often called {\textquotedblleft}predictive analytics{\textquotedblright} 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."
}
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<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.</abstract>
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%0 Conference Proceedings
%T Predictive Modeling: Guessing the NLP Terms of Tomorrow
%A Francopoulo, Gil
%A Mariani, Joseph
%A Paroubek, Patrick
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC‘16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F francopoulo-etal-2016-predictive
%X 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.
%U https://aclanthology.org/L16-1052/
%P 336-343
Markdown (Informal)
[Predictive Modeling: Guessing the NLP Terms of Tomorrow](https://aclanthology.org/L16-1052/) (Francopoulo et al., LREC 2016)
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).