Geodesic
Topic models with sentiment priors based on distributed representations
Zapiski Nauchnykh Seminarov POMI, Investigations on applied mathematics and informatics. Part I, Tome 499 (2021), pp. 284-301

Voir la notice de l'article provenant de la source Math-Net.Ru

In recent works, topic models for aspect-based opinion mining have been extended to automatically train sentiment priors for topic-word distributions, leading to automated discovery of sentiment words and improved sentiment classification. In this work, we propose an approach where sentiment priors are trained in the space of word embeddings; this allows us to both discover more aspect-related sentiment words and further improve classification. We also present an experimental study that validates our results. 
@article{ZNSL_2021_499_a15,
     author = {E. Tutubalina and S. I. Nikolenko},
     title = {Topic models with sentiment priors based on distributed representations},
     journal = {Zapiski Nauchnykh Seminarov POMI},
     pages = {284--301},
     publisher = {mathdoc},
     volume = {499},
     year = {2021},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ZNSL_2021_499_a15/}
}
TY  - JOUR
AU  - E. Tutubalina
AU  - S. I. Nikolenko
TI  - Topic models with sentiment priors based on distributed representations
JO  - Zapiski Nauchnykh Seminarov POMI
PY  - 2021
SP  - 284
EP  - 301
VL  - 499
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/ZNSL_2021_499_a15/
LA  - en
ID  - ZNSL_2021_499_a15
ER  - 
%0 Journal Article
%A E. Tutubalina
%A S. I. Nikolenko
%T Topic models with sentiment priors based on distributed representations
%J Zapiski Nauchnykh Seminarov POMI
%D 2021
%P 284-301
%V 499
%I mathdoc
%U http://geodesic.mathdoc.fr/item/ZNSL_2021_499_a15/
%G en
%F ZNSL_2021_499_a15
E. Tutubalina; S. I. Nikolenko. Topic models with sentiment priors based on distributed representations. Zapiski Nauchnykh Seminarov POMI, Investigations on applied mathematics and informatics. Part I, Tome 499 (2021), pp. 284-301. http://geodesic.mathdoc.fr/item/ZNSL_2021_499_a15/