English

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

Machine Learning 2021-03-03 v1 Computation and Language Information Retrieval

Abstract

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.

Keywords

Cite

@article{arxiv.2103.01576,
  title  = {FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs},
  author = {Jan Portisch and Michael Hladik and Heiko Paulheim},
  journal= {arXiv preprint arXiv:2103.01576},
  year   = {2021}
}