@inproceedings{mishra-etal-2019-dataset,
title = "Dataset for Aspect Detection on Mobile reviews in {H}indi",
author = "Mishra, Pruthwik and
Joshi, Ayush and
Sharma, Dipti",
editor = "Sharma, Dipti Misra and
Bhattacharya, Pushpak",
booktitle = "Proceedings of the 16th International Conference on Natural Language Processing",
month = dec,
year = "2019",
address = "International Institute of Information Technology, Hyderabad, India",
publisher = "NLP Association of India",
url = "https://aclanthology.org/2019.icon-1.15",
pages = "130--134",
abstract = "In recent years Opinion Mining has become one of the very interesting fields of Language Processing. To extract the gist of a sentence in a shorter and efficient manner is what opinion mining provides. In this paper we focus on detecting aspects for a particular domain. While relevant research work has been done in aspect detection in resource rich languages like English, we are trying to do the same in a relatively resource poor Hindi language. Here we present a corpus of mobile reviews which are labelled with carefully curated aspects. The motivation behind Aspect detection is to get information on a finer level about the data. In this paper we identify all aspects related to the gadget which are present on the reviews given online on various websites. We also propose baseline models to detect aspects in Hindi text after conducting various experiments.",
}
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%0 Conference Proceedings
%T Dataset for Aspect Detection on Mobile reviews in Hindi
%A Mishra, Pruthwik
%A Joshi, Ayush
%A Sharma, Dipti
%Y Sharma, Dipti Misra
%Y Bhattacharya, Pushpak
%S Proceedings of the 16th International Conference on Natural Language Processing
%D 2019
%8 December
%I NLP Association of India
%C International Institute of Information Technology, Hyderabad, India
%F mishra-etal-2019-dataset
%X In recent years Opinion Mining has become one of the very interesting fields of Language Processing. To extract the gist of a sentence in a shorter and efficient manner is what opinion mining provides. In this paper we focus on detecting aspects for a particular domain. While relevant research work has been done in aspect detection in resource rich languages like English, we are trying to do the same in a relatively resource poor Hindi language. Here we present a corpus of mobile reviews which are labelled with carefully curated aspects. The motivation behind Aspect detection is to get information on a finer level about the data. In this paper we identify all aspects related to the gadget which are present on the reviews given online on various websites. We also propose baseline models to detect aspects in Hindi text after conducting various experiments.
%U https://aclanthology.org/2019.icon-1.15
%P 130-134
Markdown (Informal)
[Dataset for Aspect Detection on Mobile reviews in Hindi](https://aclanthology.org/2019.icon-1.15) (Mishra et al., ICON 2019)
ACL
- Pruthwik Mishra, Ayush Joshi, and Dipti Sharma. 2019. Dataset for Aspect Detection on Mobile reviews in Hindi. In Proceedings of the 16th International Conference on Natural Language Processing, pages 130–134, International Institute of Information Technology, Hyderabad, India. NLP Association of India.