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Tax Knowledge Graph for a Smarter and More Personalized TurboTax

2020/09/13 by Jay Yu, Yu, Jay, Kevin McCluskey +3 · 1 citation
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Auction Theory and Applications #FOS: Computer and information sciences #Recommender Systems and Techniques #Semantic Web and Ontologies

paper · pdf · doi:10.48550/arxiv.2009.06103

openalex publication_date 2020/09/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Most knowledge graph use cases are data-centric, focusing on representing data entities and their semantic relationships. There are no published success stories to represent large-scale complicated business logic with knowledge graph technologies. In this paper, we will share our innovative and practical approach to representing complicated U.S. and Canadian income tax compliance logic (calculations and rules) via a large-scale knowledge graph. We will cover how the Tax Knowledge Graph is constructed and automated, how it is used to calculate tax refunds, reasoned to find missing info, and navigated to explain the calculated results. The Tax Knowledge Graph has helped transform Intuit's flagship TurboTax product into a smart and personalized experience, accelerating and automating the tax preparation process while instilling confidence for millions of customers.

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