@inproceedings{mathew-etal-2017-adapting,
title = "Adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences",
author = "Mathew, Binny and
Maity, Suman Kalyan and
Sarkar, Pratip and
Mukherjee, Animesh and
Goyal, Pawan",
editor = "Riedl, Martin and
Somasundaran, Swapna and
Glava{\v{s}}, Goran and
Hovy, Eduard",
booktitle = "Proceedings of {T}ext{G}raphs-11: the Workshop on Graph-based Methods for Natural Language Processing",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2402",
doi = "10.18653/v1/W17-2402",
pages = "11--20",
abstract = "Word senses are not static and may have temporal, spatial or corpus-specific scopes. Identifying such scopes might benefit the existing WSD systems largely. In this paper, while studying corpus specific word senses, we adapt three existing predominant and novel-sense discovery algorithms to identify these corpus-specific senses. We make use of text data available in the form of millions of digitized books and newspaper archives as two different sources of corpora and propose automated methods to identify corpus-specific word senses at various time points. We conduct an extensive and thorough human judgement experiment to rigorously evaluate and compare the performance of these approaches. Post adaptation, the output of the three algorithms are in the same format and the accuracy results are also comparable, with roughly 45-60{\%} of the reported corpus-specific senses being judged as genuine.",
}
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<abstract>Word senses are not static and may have temporal, spatial or corpus-specific scopes. Identifying such scopes might benefit the existing WSD systems largely. In this paper, while studying corpus specific word senses, we adapt three existing predominant and novel-sense discovery algorithms to identify these corpus-specific senses. We make use of text data available in the form of millions of digitized books and newspaper archives as two different sources of corpora and propose automated methods to identify corpus-specific word senses at various time points. We conduct an extensive and thorough human judgement experiment to rigorously evaluate and compare the performance of these approaches. Post adaptation, the output of the three algorithms are in the same format and the accuracy results are also comparable, with roughly 45-60% of the reported corpus-specific senses being judged as genuine.</abstract>
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%0 Conference Proceedings
%T Adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences
%A Mathew, Binny
%A Maity, Suman Kalyan
%A Sarkar, Pratip
%A Mukherjee, Animesh
%A Goyal, Pawan
%Y Riedl, Martin
%Y Somasundaran, Swapna
%Y Glavaš, Goran
%Y Hovy, Eduard
%S Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F mathew-etal-2017-adapting
%X Word senses are not static and may have temporal, spatial or corpus-specific scopes. Identifying such scopes might benefit the existing WSD systems largely. In this paper, while studying corpus specific word senses, we adapt three existing predominant and novel-sense discovery algorithms to identify these corpus-specific senses. We make use of text data available in the form of millions of digitized books and newspaper archives as two different sources of corpora and propose automated methods to identify corpus-specific word senses at various time points. We conduct an extensive and thorough human judgement experiment to rigorously evaluate and compare the performance of these approaches. Post adaptation, the output of the three algorithms are in the same format and the accuracy results are also comparable, with roughly 45-60% of the reported corpus-specific senses being judged as genuine.
%R 10.18653/v1/W17-2402
%U https://aclanthology.org/W17-2402
%U https://doi.org/10.18653/v1/W17-2402
%P 11-20
Markdown (Informal)
[Adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences](https://aclanthology.org/W17-2402) (Mathew et al., TextGraphs 2017)
ACL