@inproceedings{stefanovitch-2022-team,
title = "Team {TMA} at {S}em{E}val-2022 Task 8: Lightweight and Language-Agnostic News Similarity Classifier",
author = "Stefanovitch, Nicolas",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.166",
doi = "10.18653/v1/2022.semeval-1.166",
pages = "1178--1183",
abstract = "We present our contribution to the SemEval 22 Share Task 8: Multilingual news article similarity. The approach is lightweight and language-agnostic, it is based on the computation of several lexicographic and embedding-based features, and the use of a simple ML approach: random forests. In a notable departure from the task formulation, which is a ranking task, we tackled this task as a classification one. We present a detailed analysis of the behaviour of our system under different settings.",
}
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<abstract>We present our contribution to the SemEval 22 Share Task 8: Multilingual news article similarity. The approach is lightweight and language-agnostic, it is based on the computation of several lexicographic and embedding-based features, and the use of a simple ML approach: random forests. In a notable departure from the task formulation, which is a ranking task, we tackled this task as a classification one. We present a detailed analysis of the behaviour of our system under different settings.</abstract>
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%0 Conference Proceedings
%T Team TMA at SemEval-2022 Task 8: Lightweight and Language-Agnostic News Similarity Classifier
%A Stefanovitch, Nicolas
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F stefanovitch-2022-team
%X We present our contribution to the SemEval 22 Share Task 8: Multilingual news article similarity. The approach is lightweight and language-agnostic, it is based on the computation of several lexicographic and embedding-based features, and the use of a simple ML approach: random forests. In a notable departure from the task formulation, which is a ranking task, we tackled this task as a classification one. We present a detailed analysis of the behaviour of our system under different settings.
%R 10.18653/v1/2022.semeval-1.166
%U https://aclanthology.org/2022.semeval-1.166
%U https://doi.org/10.18653/v1/2022.semeval-1.166
%P 1178-1183
Markdown (Informal)
[Team TMA at SemEval-2022 Task 8: Lightweight and Language-Agnostic News Similarity Classifier](https://aclanthology.org/2022.semeval-1.166) (Stefanovitch, SemEval 2022)
ACL