  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.
