publication . Conference object . 2014

Semi-Automatic Construction of Skeleton Concept Maps from Case Judgments

Boer, A.; Sijtsma, B.; Winkels, R.; Lettieri, N.;
Open Access English
  • Published: 01 Jan 2014
  • Publisher: [S.n.]
  • Country: Netherlands
Abstract
This paper proposes an approach to generating Skeleton Conceptual Maps (SCM) semi automatically from legal case documents provided by the United Kingdom’s Supreme Court. SCM are incomplete knowledge representations for the purpose of scaffolding learning. The proposed system intends to provide students with a tool to pre-process text and to extract knowledge from documents in a time saving manner. A combination of natural language processing methods and proposition extraction algorithms are used to generate the output. Conclusion is that improvements are necessary to provide results that adequately support students.
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21 references, page 1 of 2

[1] A. Cicognani et al. Concept mapping as a collaborative tool for enhanced online learning. Educational Technology & Society, 3(3):150-158, 2000.

[2] R. Clariana and R. Koul. A computer-based approach for translating text into concept map-like representations. In Proceedings of the first international conference on concept mapping, pages 14-17, 2004. [OpenAIRE]

[3] U. K. S. Court. Secretary of state for home department (appellant) v mn and ky (respondents) (scotland). http://supremecourt.uk/decided-cases/docs/UKSC_2013_ 0202_Judgment.pdf, 2014. [Online; accessed 05-June-2014].

[4] U. K. S. Court. Summary: Secretary of state for home department (appellant) v mn and ky (respondents) (scotland). http://supremecourt.uk/decided-cases/docs/UKSC_2013_ 0202_PressSummary.pdf, 2014. [Online; accessed 05-June-2014].

[5] M. J. Eppler. A comparison between concept maps, mind maps, conceptual diagrams, and visual metaphors as complementary tools for knowledge construction and sharing. Information Visualization, 5(3):202-210, 2006. [OpenAIRE]

[6] A. Fader, S. Soderland, and O. Etzioni. Identifying relations for open information extraction. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 1535-1545. Association for Computational Linguistics, 2011.

[7] F. Fischer, J. Bruhn, C. Gra¨sel, and H. Mandl. Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12(2):213-232, 2002.

[8] J. H. Kowata, D. Cury, and M. C. S. Boeres. Concept maps core elements candidates recognition from text. In Proceedings of Fourth International Conference on Concept Mapping, Vin˜a del Mar, Chile, pages 120-127. Citeseer, 2010.

[9] A. V. D. Leake. Jump-starting concept map construction with knowledge extracted from documents. In In Proceedings of the Second International Conference on Concept Mapping (CMC. Citeseer, 2006.

[10] K. M. Markham, J. J. Mintzes, and M. G. Jones. The concept map as a research and evaluation tool: Further evidence of validity. Journal of research in science teaching, 31(1):91-101, 1994. [OpenAIRE]

[11] G. A. Miller. Wordnet: A lexical database for english. Commun. ACM, 38(11):39-41, Nov. 1995.

[12] A. J. Muntjewerff and J. A. Breuker. Evaluating prosa, a system to train solving legal cases. In Proc. of AIED, pages 278-285, 2001.

[13] J. D. Novak. Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Routledge, 2010.

[14] J. D. Novak and A. J. Can˜as. The origins of the concept mapping tool and the continuing evolution of the tool. Information Visualization, 5(3):175-184, 2006.

[15] J. D. Novak and A. J. Can˜as. The theory underlying concept maps and how to construct them. Florida Institute for Human and Machine Cognition, 1, 2006.

21 references, page 1 of 2
Abstract
This paper proposes an approach to generating Skeleton Conceptual Maps (SCM) semi automatically from legal case documents provided by the United Kingdom’s Supreme Court. SCM are incomplete knowledge representations for the purpose of scaffolding learning. The proposed system intends to provide students with a tool to pre-process text and to extract knowledge from documents in a time saving manner. A combination of natural language processing methods and proposition extraction algorithms are used to generate the output. Conclusion is that improvements are necessary to provide results that adequately support students.
Related Organizations
Download from
21 references, page 1 of 2

[1] A. Cicognani et al. Concept mapping as a collaborative tool for enhanced online learning. Educational Technology & Society, 3(3):150-158, 2000.

[2] R. Clariana and R. Koul. A computer-based approach for translating text into concept map-like representations. In Proceedings of the first international conference on concept mapping, pages 14-17, 2004. [OpenAIRE]

[3] U. K. S. Court. Secretary of state for home department (appellant) v mn and ky (respondents) (scotland). http://supremecourt.uk/decided-cases/docs/UKSC_2013_ 0202_Judgment.pdf, 2014. [Online; accessed 05-June-2014].

[4] U. K. S. Court. Summary: Secretary of state for home department (appellant) v mn and ky (respondents) (scotland). http://supremecourt.uk/decided-cases/docs/UKSC_2013_ 0202_PressSummary.pdf, 2014. [Online; accessed 05-June-2014].

[5] M. J. Eppler. A comparison between concept maps, mind maps, conceptual diagrams, and visual metaphors as complementary tools for knowledge construction and sharing. Information Visualization, 5(3):202-210, 2006. [OpenAIRE]

[6] A. Fader, S. Soderland, and O. Etzioni. Identifying relations for open information extraction. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 1535-1545. Association for Computational Linguistics, 2011.

[7] F. Fischer, J. Bruhn, C. Gra¨sel, and H. Mandl. Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12(2):213-232, 2002.

[8] J. H. Kowata, D. Cury, and M. C. S. Boeres. Concept maps core elements candidates recognition from text. In Proceedings of Fourth International Conference on Concept Mapping, Vin˜a del Mar, Chile, pages 120-127. Citeseer, 2010.

[9] A. V. D. Leake. Jump-starting concept map construction with knowledge extracted from documents. In In Proceedings of the Second International Conference on Concept Mapping (CMC. Citeseer, 2006.

[10] K. M. Markham, J. J. Mintzes, and M. G. Jones. The concept map as a research and evaluation tool: Further evidence of validity. Journal of research in science teaching, 31(1):91-101, 1994. [OpenAIRE]

[11] G. A. Miller. Wordnet: A lexical database for english. Commun. ACM, 38(11):39-41, Nov. 1995.

[12] A. J. Muntjewerff and J. A. Breuker. Evaluating prosa, a system to train solving legal cases. In Proc. of AIED, pages 278-285, 2001.

[13] J. D. Novak. Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Routledge, 2010.

[14] J. D. Novak and A. J. Can˜as. The origins of the concept mapping tool and the continuing evolution of the tool. Information Visualization, 5(3):175-184, 2006.

[15] J. D. Novak and A. J. Can˜as. The theory underlying concept maps and how to construct them. Florida Institute for Human and Machine Cognition, 1, 2006.

21 references, page 1 of 2
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