Mining e-contract documents to classify clauses

ABSTRACT

E-contracts begin as legal documents and end up as processes that help organizations abide by legal rules while fulfilling contract terms. As contracts are complex, their deployment is predominantly established and fulfilled with significant human involvement. One of the key difficulties with any kind of contract processing is the legal ambiguity, which makes it difficult to address any violation of the contract terms. Thus, there is a need to track clauses for the contract activities under execution and violation of clauses. This necessitates deriving clause patterns from e-contract documents and map to their respective activities for further monitoring and fulfillment of e-contracts during their enactment. In this paper, we present a classification approach to extract clause patterns from e-contract documents. This is a challenging task as activities and clauses are mostly derived from both legal and business process driven contract knowledge.

References

1. R. Bekkerman and J. Allan. Using bigrams in text categorization. Technical Report IR-408, Center of Intelligent Information Retrieval, UMass Amherst, 2004.
2. H. L. Cardoso and E. Oliveira. Assisting and regulating virtual enterprise interoperability through contracts. 2008.
3. J. Cole and Z. Milosevic. Extending support for contracts in ebxml. In ITVE '01: Proceedings of the workshop on Information technology for virtual enterprises, pages 119--127, Washington, DC, USA, 2001. IEEE Computer Society.
4. A. Daskalopulu. Logic-Based Tools for the Analysis and Representation of Legal Contracts. PhD thesis, Imperial College London, 1999.
5. A. Daskalopulu and M. Sergot. The representation of legal contracts. AI Soc., 11(1--2):6--17, 1997.
6. M. Fantinato, I. M. de Souza Gimenes, and M. B. F. de Toledo. Web service e-contract establishment using features. In S. Dustdar, J. L. Fiadeiro, and A. P. Sheth, editors, Business Process Management, volume 4102 of Lecture Notes in Computer Science, pages 290--305. Springer, 2006.
7. M. Fantinato, M. B. F. de Toledo, and I. M. d. S. Gimenes. A feature-based approach to electronic contracts. In CEC-EEE '06: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services, page 34, Washington, DC, USA, 2006. IEEE Computer Society.
8. B. N. Grosof, Y. Labrou, and H. Y. Chan. A declarative approach to business rules in contracts: courteous logic programs in xml. In EC '99: Proceedings of the 1st ACM conference on Electronic commerce, pages 68--77, New York, NY, USA, 1999. ACM.
9. S. Gunn. Support vector machine for classification and regression. Technical report, University of Southampton, 2005.
10. K. Karlapalem, A. R. Dani, and P. R. Krishna. A frame work for modeling electronic contracts. In ER'01: Proceedings of the 20th International Conference on Conceptual Modeling, pages 193--207, London, UK, 2001. Springer-Verlag.
11. M. Koetsier, P. W. P. J. Grefen, and J. Vonk. Contracts for cross-organizational workflow management. In EC-WEB '00: Proceedings of the First International Conference on Electronic Commerce and Web Technologies, pages 110--121, London, UK, 2000. Springer-Verlag.
12. P. R. Krishna, K. Karlapalem, and D. K. W. Chiu. An EREC framework for e-contract modeling, enactment and monitoring. Data Knowl. Eng., 51(1):31--58, 2004.
13. T. Kwok and T. Nguyen. An enterprise electronic contract management system using dual xml and secure pdf documents. In EDOCW '06: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops, page 57, Washington, DC, USA, 2006. IEEE Computer Society.
14. P. F. Linington. Automating support for e-business contracts, September 2005.
15. J. B. Lovins. Development of a stemming algorithm. Mechanical Translation and Computational Linguistics, 11:22--31, 1968.
16. C. Molina-Jimenez, S. Shrivastava, E. Solaiman, and J. Warne. Contract representation for run-time monitoring and enforcement. E-Commerce Technology, IEEE International Conference on, 0:103, 2003.
17. C. Molina-Jiménez, S. K. Shrivastava, E. Solaiman, and J. P. Warne. Run-time monitoring and enforcement of electronic contracts. Electronic Commerce Research and Applications, 3(2):108--125, 2004.
18. M. Rouached, O. Perrin, and C. Godart. A contract-based approach for monitoring collaborative web services using commitments in the event calculus. In A. H. H. Ngu, M. Kitsuregawa, E. J. Neuhold, J.-Y. Chung, and Q. Z. Sheng, editors, WISE, volume 3806 of Lecture Notes in Computer Science, pages 426--434. Springer, 2005.
19. C.-M. Tan, Y.-F. Wang, and C.-D. Lee. The use of bigrams to enhance text categorization. Inf. Process. Manage., 38(4):529--546, 2002.
20. S. Varadarajan, K. Kasravi, and R. Feldman. Text-mining: Application development challenges. In 22nd International conference on Knowledge Based Systems and applied Artificial Intelligence (ES02), Springer Verlag, 2002.

• Computing methodologies

  • Machine learning

    • Learning paradigms

      • Supervised learning

    • Machine learning approaches