# FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs

arXiv: https://arxiv.org/abs/2103.01576 · HTML: https://mlsanity.com/paper/2103.01576/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 24 references that are in the map.
- First posted on arXiv 2 Mar 2021.

## Builds on (most cited first, 6 of 6)

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [RDF2Vec Light -- A Lightweight Approach for Knowledge Graph Embeddings](https://mlsanity.com/paper/2009.07659/) (2020)
- [KGvec2go -- Knowledge Graph Embeddings as a Service](https://mlsanity.com/paper/2003.05809/) (2020)
- [Supervised Ontology and Instance Matching with MELT](https://mlsanity.com/paper/2009.11102/) (2020)
- [Visual Analysis of Ontology Matching Results with the MELT Dashboard](https://mlsanity.com/paper/2004.12628/) (2020)

## Built on by (most cited first, 2 of 2)

- [Term Expansion and FinBERT fine-tuning for Hypernym and Synonym Ranking of Financial Terms](https://mlsanity.com/paper/2107.13764/) (2021)
- [Learning Semantic Text Similarity to rank Hypernyms of Financial Terms](https://mlsanity.com/paper/2303.13475/) (2023)

## Abstract (arXiv)

This paper presents the FinMatcher system and its results for the FinSim 2021 shared task which is co-located with the Workshop on Financial Technology on the Web (FinWeb) in conjunction with The Web Conference. The FinSim-2 shared task consists of a set of concept labels from the financial services domain. The goal is to find the most relevant top-level concept from a given set of concepts. The FinMatcher system exploits three publicly available knowledge graphs, namely WordNet, Wikidata, and WebIsALOD. The graphs are used to generate explicit features as well as latent features which are fed into a neural classifier to predict the closest hypernym.