Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 583-590.doi: 10.11896/JsJkx.190900140
• Interdiscipline & Application • Previous Articles Next Articles
ZHOU Wei1 and LUO Xu-dong2
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[1] CORTES P,LODDER A R.Consumer dispute resolution goes online:reflections on the evolution of European law for out-of-court redress.Maastricht Journal of European and Comparative Law,2014,21(1):14-38. [2] LIU M D.On dispute’s online resolution.Legal Science,2002(8):44-51. [3] SCHULTZ T.Online dispute resolution:an overview and selec-ted issues.(2002-6-7) .https://ssrn.com/abstract=898821. [4] SMITH S,MARTINEZ J.An analytic framework for dispute systems design.Harvard Negotiation Law Review,2009,14:123-169. [5] BEX F,PRAKKEN H,VAN ENGERS T,et al.Introduction to the special issue on artificial intelligence for Justice (AI4J).Artificial Intelligence and Law,2017,25(1):1-3. [6] HUANG X T,LUO X D.State-of-the-art and development trend of artificial intelligence combined with law.Computer Science,2018,45(12):1-11. [7] CARNEIRO D,NOVAIS P,ANDRADE F,et al.Online dispute resolution:An artificial intelligence perspective.Artificial Intelligence Review,2014,41(2):211-240. [8] BUCHANAN B G,HEADRICK T E.Some speculation about artificial intelligence and legal reasoning.Stanford Law Review,1970,23(1):40-62. [9] WALTON D,GODDEN D M.Persuasion dialogue in online dispute resolution.Artificial Intelligence and Law,2005,13(2):273-295. [10] LODDER A R,THIESSEN E M.The role of artificial intelligence in online dispute resolution//Workshop on Online Dispute Resolution at the International Conference on Artificial Intelligence and Law.Edinburgh,UK,2003. [11] BELLUCCI E,LODDER A R,ZELEZNIKOW J.Integrating artificial intelligence,argumentation and game theory to develop an online dispute resolution environment//Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence.IEEE Computer Society,2004. [12] KOULU A R.Blockchains and online dispute resolution:smart contracts as an alternative to enforcement.A Journal of Law,Technology & Society,2016,13(1):40-69. [13] ETHAN K,JANET R.Online dispute resolution,resolving conflicts in cyberspace.Artificial Intelligence and Law,2003,11(1):69-75. [14] ZHOU Y B,CAO P Z.On Internet+era online arbitration mechanism construction-the core of arbitration theory of denationalized.Enterprise Economy,2019(4):149-153. [15] ZHONG C.The Method of Internet+Commerce Dispute Resolution-The View from “Cloud Arbitration” of Shenzhen.Special Zone Economy,2018(5):138-140. [16] ASHLEY K D.Artificial Intelligence and Legal Analytics:New Tools for Law Practice in the Digital Age.United States of America:Cambridge University Press,2017:426. [17] ZHONG Q,FAN X,LUO X D,et al.An explainable multi-attribute decision model based on argumentation.Expert Systems with Applications,2019,117:42-61. [18] TANG X B.Management Information System.BeiJing:Science Press,2005:7-8. [19] ALBORNOZ M M,MARTIN N G.Feasibility analysis of online dispute resolution in developing countries .University of Mia-mi Inter-American Law Review,2012,44(2):39-61. [20] FENG W D,CHEN J,FENG T J,et al.Organizational design process modeling and its implementing on virtual enterprises.Computer Integrated Manufacturing Systems,2000,6(3):17-24. [21] TANG L.On the misinterpretation and correction of procedure for forming an arbitral tribunal:based on game theory.Journal of Southwest University of Political Science and Law,2014,16(2):86-95. [22] ZHOU W.Analysis on the functional mechanism of big data in fact finding.Journal of China University of Political Science and Law,2015(6):64-82. [23] SHAO Q F,JIN C Q,ZHANG Z,et al.Blockchain:architecture and research progress.Chinese Journal of Computers,2018,41(5):969-988. [24] LI G,MA Y X,BA Z C.Theoretical thinking of data management based on value chain.Journal of Information Resources Management,2018,8(1):9-18. [25] JIANG L L.The legal nature of Chinese arbitral institution and its reform.Journal of Comparative Law,2019(3):142-156. |
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