Conversation Concepts: Understanding Topics and Building Taxonomies for Financial Services

John P Mccrae,Paul Buitelaar,Saurav Karmakar,Siddharth Narayanan,Bianca Pereira,Rajdeep Sarkar,Pranab Mohanty

doi:10.3390/info12040160

Abstract

Knowledge graphs are proving to be an increasingly important part of modern enterprises, and new applications of such enterprise knowledge graphs are still being found. In this paper, we report on the experience with the use of an automatic knowledge graph system called Saffron in the context of a large financial enterprise and show how this has found applications within this enterprise as part of the “Conversation Concepts Artificial Intelligence” tool. In particular, we analyse the use cases for knowledge graphs within this enterprise, and this led us to a new extension to the knowledge graph system. We present the results of these adaptations, including the introduction of a semi-supervised taxonomy extraction system, which includes analysts in-the-loop. Further, we extend the kinds of relations extracted by the system and show how the use of the BERTand ELMomodels can produce high-quality results. Thus, we show how this tool can help realize a smart enterprise and how requirements in the financial industry can be realised by state-of-the-art natural language processing technologies.

Highlights

BuscaldiEnterprise knowledge graphs [1] are a key tool that can enable businesses to create smart artificial-intelligence-driven applications that can bring real business value
We present our solution to and experiences with this problem, drawn from a collaborative project between an academic institution, the National University of Ireland (NUI) Galway, and an enterprise, FMR LLC
With the help of a domain knowledge graph/ontology, our objective is to identify entities and break down complex utterances into “context/description” and “request”

Summary

Introduction

BuscaldiEnterprise knowledge graphs [1] are a key tool that can enable businesses to create smart artificial-intelligence-driven applications that can bring real business value. We present our solution to and experiences with this problem, drawn from a collaborative project between an academic institution, the National University of Ireland (NUI) Galway, and an enterprise, FMR LLC This collaboration builds firstly on the work of the Insight SFIResearch Centre for Data Analytics at NUI Galway’s experience with the creation of knowledge graphs and, in particular, the system called Saffron [2]. This system is designed to create a taxonomy automatically from a large text corpus and works by first identifying all the terms using syntactic and corpus frequency information. Relationships between these terms are found, and these terms are organized into a taxonomy structure

Objectives

Discussion

Conclusion