Abstract
In this paper, we argue for the necessity of constructing an ontology which represents the U.S. Internal Revenue Code (IRC). Doing so would enable the construction of a broad range of intelligent applications, including automatic auditing software, robust on-line help systems, and tax question-answering systems. In this paper, we propose the construction of a rich ontology which models the tax code. We examine some of the unique challenges presented by a tax ontology and provide examples of the types of knowledge necessary for such an ontology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
The Internal Revenue Code (2004), http://www.fourmilab.ch/ustax/ustax.html
GAO-02-711R IRS Budget Justification Options. General Accounting Office Washington, DC (2002), www.unclefed.com/GAOReports/d02711r.pdf
TurboTax, www.intuit.com
Genesereth, M.: Knowledge Interchange Format specification (1995), http://logic.stanford.edu/kif/specification.html
PowerLoom Knowledge Representation System (2004), http://www.isi.edu/isd/LOOM/PowerLoom/
FrameNet (2004), http://www.icsi.berkeley.edu/~framenet/
Cyc (2004), http://www.cyc.com
OpenMind (2004), http://www.openmind.org/
Chalupsky, H.: WhyNot: debugging failed queries in large knowledge bases. In: Proceedings of the Eighteenth national conference on Artificial Intelligence (2002)
Mommers, L.: Applied legal epistemology: building a knowledge-based ontology of the legal domain, Ph.D. thesis (2002)
Valente, A., Russ, T., MacGregor, R., Swartout, W.: Building, Using and Reusing an Ontology of Air Campaign Planning. IEEE Intelligent Systems 14(1), 27–36 (1999)
Valente, A., Breuker, J.: Legal Modelling and Automated Reasoning with ON-LINE. International Journal of Human-Computer Studies 51(6), 1079–1125 (1999)
Valente, A., Breuker, J.: Towards Principled Core Ontologies. In: Gaines, B., Musen, M. (eds.) Proceedings of the Tenth Knowledge Acquisition for Knowledge-Based Systems Workshop (KAW 1996), Banff, pp. 33/1–33/20 (1996)
McCarty, T.: A language for legal discourse I. basic structures. In: Proc. of the Second International Conference on AI and Law, Vancouver, pp. 180–189. ACM, New York (1989)
Valente, A.: Roles and Uses of Ontologies in AI and Law. In: Law and the Semantic Web, Springer, Heidelberg (2004) (in press)
Benjamins, V.R., Contreras, J., Casanovas, P., Ayuso, M.: Ontologies of Professional Legal Knowledge as the Basis for Intelligent IT Support for Judges. In: Proceedings of the ICAIL 2003 Workshop on Legal Ontologies & Web based legal information management (2003)
Visser, P.S., Bench-Capon, T.M.: A Comparison of Four Ontologies for the Design of Legal Knowledge Systems. Artificial Intelligence and Law 6, 25–57 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Melz, E., Valente, A. (2004). Modeling the Tax Code. In: Meersman, R., Tari, Z., Corsaro, A. (eds) On the Move to Meaningful Internet Systems 2004: OTM 2004 Workshops. OTM 2004. Lecture Notes in Computer Science, vol 3292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30470-8_76
Download citation
DOI: https://doi.org/10.1007/978-3-540-30470-8_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23664-1
Online ISBN: 978-3-540-30470-8
eBook Packages: Springer Book Archive