DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features
Abstract
We present the submission of team DICoE for FinSim-3, the 3rd Shared Task on Learning Semantic Similarities for the Financial Domain. The task provides a set of terms in the financial domain and requires to classify them into the most relevant hypernym from a financial ontology. After augmenting the terms with their Investopedia definitions, our system employs a Logistic Regression classifier over financial word embeddings and a mix of hand-crafted and distance-based features. Also, for the first time in this task, we employ different replacement methods for out-of-vocabulary terms, leading to improved performance. Finally, we have also experimented with word representations generated from various financial corpora. Our best-performing submission ranked 4th on the task's leaderboard.
Cite
@article{arxiv.2109.14906,
title = {DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features},
author = {Lefteris Loukas and Konstantinos Bougiatiotis and Manos Fergadiotis and Dimitris Mavroeidis and Elias Zavitsanos},
journal= {arXiv preprint arXiv:2109.14906},
year = {2023}
}
Comments
6 pages, Proceedings of the Third Workshop on Financial Technology and Natural Language Processing (FinNLP@IJCAI-2021)