LGDM Approaches and Models: A Literature Review

  • Iván Palomares Carrascosa
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)


Once the foundations and main considerations for Large Group Decision Making have been set out, this chapter provides a comprehensive literature review of most of its related works in the scientific literature to date. The reviewed studies are categorized into subgroup clustering methods, Large Group Decision Making methods (for preference aggregation and weighting), consensus approaches, behavior management and modeling methodologies, and theory/interdisciplinary approaches.



The author and contributors of this chapter would like to thank those colleagues across the LGDM and related scientific communities who willingly shared their original graphical material during the elaboration of the literature survey, specially to: Yucheng Dong (Sichuan University, China), Bingsheng Liu (Chongqing University, China), Victoria López (Complutense University of Madrid, Spain), Ramón Soto (Sonora University, Mexico), Xunjie Gou and Francisco Herrera (University of Granada, Spain), Ashish Goel and David T. Lee (Stanford University, US).


  1. 2.
    Alonso, S., Pérez, I.J., Cabrerizo, F.J., Herrera-Viedma, E.: A Fuzzy Group Decision Making Model for Large Groups of Individuals. In: Proceedings of FUZZ-IEEE 2009, pp. 643–648, 2009.Google Scholar
  2. 3.
    Arrow, K.J.: A difficulty in the concept of social welfare. Journal of Political Economy, 58(4), pp. 328–346, 1950.CrossRefGoogle Scholar
  3. 5.
    B’́ack, E., Esaiasson, P., Gilljam, M., Svenson, O., Lindholm, T.: Post-Decision Consolidation in Large Group decision-making. Cognition and Neurosciences. Scandinavian Journal of Psychology, 52, pp. 320–328, 2011.CrossRefGoogle Scholar
  4. 8.
    Beliakov, G., Pradera, A., Calvo, T.: Aggregation functions: a guide for practitioners. Springer Studies in Fuzziness and Soft Computing (reprint), Springer, 2010.Google Scholar
  5. 12.
    Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008 (10), pp. 1–12, 2008.CrossRefGoogle Scholar
  6. 13.
    Bolloju, N.: Aggregation of analytic hierarchy process models based on similarities in decision makers’ preferences. European Journal of Operational Research, 128, pp. 499–508, 2001.CrossRefGoogle Scholar
  7. 19.
    Cai, C.-G., Xu, X.-H., Wang, P., Chen, X.-H.: A multi-stage conflict style large group emergency decision-making method. Soft Computing, 21, pp. 5765–5778, 2017.CrossRefGoogle Scholar
  8. 20.
    Campanella, G., Ribeiro, R.: A framework for dynamic multiple-criteria decision making. Decision Support Systems, 52, pp. 52–60, 2011.CrossRefGoogle Scholar
  9. 22.
    Carneiro, J., Saraiva, P., Martinho, D., Marreiros, G., Novais, P.: Representing decision-makers using styles of behavior: an approach designed for group decision support systems. Cognitive Systems Research, 47, pp. 109–132, 2018.CrossRefGoogle Scholar
  10. 26.
    Chavez, A., Maes, P.: Kasbah: An agent marketplace for buying and selling goods. Procs. 1st International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology, pp. 75–90, 1996.Google Scholar
  11. 32.
    Cole, J.D., Sage, A.P.: Multi-person decision analysis in large scale systems - group decision making. Journal of the Franklin Institute, Apr 1975, pp. 245–268.MathSciNetCrossRefGoogle Scholar
  12. 33.
    Crosscombe, M., Lawry, J.: Exploiting vagueness for multi-agent consensus. Multi-agent and Complex Systems, Studies in Computational Intelligence, vol. 670, pp. 67–78, Springer, 2017.Google Scholar
  13. 34.
    Dong, Y., Wu, Y., Zhang, H., Zhang, G.: Multi-granular unbalanced linguistic distribution assessments with interval symbolic proportions. Knowledge-based Systems, 82, pp. 139–151, 2015.CrossRefGoogle Scholar
  14. 36.
    Dong, Y., Zhang, H., Herrera-Viedma, E.: Integrating experts’ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decision Support Systems, 84, pp. 1–15, 2016.CrossRefGoogle Scholar
  15. 37.
    Dong, Y., Ding, Z., Martinez, L., Herrera, F.: Managing consensus based on leadership in opinion dynamics. Information Sciences, 397–298, pp. 187–205, 2016.Google Scholar
  16. 38.
    Dong, Y., Zhao, S., Zhang, H., Chiclana, F., Herrera-Viedma, E.: A self-management mechanism for non-cooperative behaviors in large-scale group consensus reaching processes. IEEE Transactions on Fuzzy Systems, In press. Scholar
  17. 39.
    Dong, Y., Zha, Q., Zhang, H., Kou, G., Fujita, H., Chiclana, F., Herrera-Viedma, E.: Consensus Reaching in Social Network Group Decision Making: Research Paradigms and Challenges. Knowledge-based Systems, In press. Scholar
  18. 45.
    French, J.R., John, R.P.: A formal theory of social power. Psychological Review, 63(3), pp. 181–194, 1956.CrossRefGoogle Scholar
  19. 48.
    Goel, A., Lee, D.T.: Towards large-scale deliberative decision-making: small groups and the importance of triads. EC ’16 Proceedings of the 2016 ACM Conference on Economics and Computation, pp. 287–303, 2016.Google Scholar
  20. 49.
    Gomes, L.F.A.M., Lima, M.P.P.: TODIM: Basic and application to multicriteria ranking of projects with environmental impacts. Foundations of Computing and Decision Sciences, 16(3), pp. 113–127, 1991.zbMATHGoogle Scholar
  21. 52.
    Gou, X., Xu, Z., Herrera, F.: Consensus Reaching Process for Large-scale Group Decision Making with Double Hierarchy Hesitant Fuzzy Linguistic Preference Relations. Knowledge-based Systems, 157, pp. 20–33, 2018.CrossRefGoogle Scholar
  22. 53.
    Gupta, M.: Consensus building process in group decision making - an adaptive procedure based on group dynamics. IEEE Transactions on Fuzzy Systems, In press. CrossRefGoogle Scholar
  23. 67.
    Kacprzyk, J.: Group decision making with a fuzzy linguistic majority. Fuzzy Sets and Systems, 18(2), pp. 105–118, 1986.MathSciNetCrossRefGoogle Scholar
  24. 74.
    Kohonen, T.: Self-organizing maps. Heidelberg, Springer, 1995.CrossRefGoogle Scholar
  25. 75.
    Labella, A., Liu, Y., Rodríguez, R.M., Martínez, L.: Analyzing the performance of classical consensus models in large scale group decision making: A comparative study. Applied Soft Computing, 67, pp. 677–690, 2018.CrossRefGoogle Scholar
  26. 78.
    Li, Y., Lian, X., Lu, C., Wang, Z.: A large group decision making approach based on TOPSIS framework with unknown weights information. MATEC Web of Conferences (13th Global Congress on Manufacturing and Management, GCMM 2016), vol. 100, 2017.CrossRefGoogle Scholar
  27. 80.
    Liu, H.C., You, X.Y., Tsung, F., Ji, P.: An improved approach for failure mode and effect analysis involving large group of experts: an application to the healthcare field. Quality Engineering, In press.
  28. 81.
    Liu, B., Shen, Y., Chen, X., Sun, H., Chen, Y.: A complex multi-attribute large-group PLS decision-making method in the interval-valued intuitionistic fuzzy environment. Applied Mathematical Modelling, 38, pp. 4512–4527, 2014.MathSciNetCrossRefGoogle Scholar
  29. 82.
    Liu, B., Huo, T., Liao, P., Gong, J., Xue, B.: A group decision-making aggregation model for contractor selection in large scale construction projects based on two-stage partial least squares (PLS) path modeling. Group Decision and Negotiation, 24(5), pp. 855–883, 2014.CrossRefGoogle Scholar
  30. 83.
    Liu, B., Shen, Y., Chen, X., Che, Y., Wang, X.: A partial binary tree DEA-DA cyclic classification model for decision makers in complex multi-attribute large-group interval-valued intuitionistic fuzzy decision-making problems. Information Fusion, 18, pp. 119–130, 2014.CrossRefGoogle Scholar
  31. 84.
    Liu, B., Chen, Y., Shen, Y., Sun, H., Xu, X.: A complex multi-attribute large-group decision making method based on the interval-valued intuitionistic fuzzy principal component analysis model. Soft Computing, 18, pp. 2149–2160, 2014.CrossRefGoogle Scholar
  32. 85.
    Liu, B., Shen, Y., Zhang, W., Chen, X., Wang, X.: An interval-valued intuitionistic fuzzy principal component analysis model-based method for complex multi-attribute large-group decision-making. European Journal of Operational Research, 245, pp. 209–225, 2015.MathSciNetCrossRefGoogle Scholar
  33. 86.
    Liu, B., Shen, Y., Chen, Y., Chen, X., Wang, Y.: A two-layer weight determination method for complex multi-attribute large-group decision-making experts in a linguistic environment. Information Fusion, 23, pp. 156–165, 2015.CrossRefGoogle Scholar
  34. 87.
    Liu, Y., Fan, Z.P., Zhang, X.: A method for large group decision-making based on evaluation information provided by participators from multiple groups. Information Fusion, 29, pp. 132–141, 2016.CrossRefGoogle Scholar
  35. 89.
    Liu, B., Guo, S., Yan, K., Li, L., Wang, X.: Double weight determination method for experts of complex multi-attribute large-group decision-making in interval-valued intuitionistic fuzzy environment. Journal of Systems Engineering and Electronics, 28(1), pp. 88–96, 2017.CrossRefGoogle Scholar
  36. 92.
    Lootsma, F.A.: Scale sensitivity in the multiplicative AHP and SMART. Journal of Multi-Criteria Decision Analysis, 2(2), pp. 87–110, 1993.CrossRefGoogle Scholar
  37. 98.
    Nyerges, T., Aguirre, R.W.: Public Participation in Analytic-Deliberative Decision Making: Evaluating a Large-Group Online Field Experiment. Annals of the Association of American Geographers, 101(3), pp. 561–586, 2011.CrossRefGoogle Scholar
  38. 102.
    Palomares, I., Quesada, F., Martinez, L.: Multi-agent-based semi-supervised consensus support system for large-scale group decision making. In Z. Wen and T. Li (eds.): Foundations of Intelligent Systems (ISKE 2013 Proceedings), Advances in Intelligent Systems and Computing 277, pp. 241–251, Springer, 2014.Google Scholar
  39. 104.
    Palomares, I., Martinez, L.: A semisupervised multiagent system model to support consensus-reaching processes. IEEE Transactions on Fuzzy Systems, 22(4), pp. 762–777, 2014.CrossRefGoogle Scholar
  40. 105.
    Palomares, I., Martínez, L., Herrera, F.: A consensus model to detect and manage non-cooperative behaviors in large-scale group decision making. IEEE Transactions on Fuzzy Systems, 22(3), pp. 516–530, 2014.CrossRefGoogle Scholar
  41. 106.
    Palomares, I., Quesada, F., Martínez, L.: An approach based on computing with words to manage experts behavior in consensus reaching processes with large groups. Procs. 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014.Google Scholar
  42. 107.
    Palomares, I., Martínez, L., Herrera, F.: MENTOR: A graphical monitoring tool of preferences evolution in large-scale group decision making. Knowledge-based Systems, 58 (Spec.Iss.), pp. 66–74, 2014.CrossRefGoogle Scholar
  43. 108.
    Palomares, I.: Multi-agent System to model consensus processes in large-scale group decision making using soft computing techniques. PhD Thesis, University of Jaén (Spain), 2014.Google Scholar
  44. 109.
    Quesada, F., Palomares, I., Martínez, L.: Managing experts behavior in large-scale consensus reaching processes with uninorm aggregation operators. Applied Soft Computing, 35, pp. 873–887, 2015.CrossRefGoogle Scholar
  45. 112.
    Palomares, I., Crosscombe, M., Chen, Z.S., Lawry, J.: Dual Consensus Measure for Multi-Perspective Multi-Criteria Group Decision Making. Proceedings of IEEE International Conference on Systems, Man and Cybernetics, IEEE SMC’18. 2018.Google Scholar
  46. 116.
    Rodríguez, M.A.: Advances towards a general-purpose societal-scale human-collective problem-solving engine. Procs. 2004 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 206–211, 2004.Google Scholar
  47. 117.
    Rodriguez, M.A.: Social decision making with multi-relational networks and grammar-based particle swarms. Procs. 40th Hawaii International Conference on System Sciences, 2007.Google Scholar
  48. 129.
    Shannon, C.E.: A mathematical theory of communication. The Bell System Technical Journal, 27, pp. 379–423, 623–656, 1948.MathSciNetCrossRefGoogle Scholar
  49. 130.
    Shi, Z.J., Wang, X.Q., Palomares, I., Guo, S.J., Ding, R.X.: A novel consensus model for multi-attribute large-scale group decision making based on comprehensive behavior Classification and adaptive weight updating. Knowledge-based Systems, In Press. CrossRefGoogle Scholar
  50. 131.
    Shum, S., Cannavacciuolo, L., De Liddo, A., Iandoli, L., Quinto, I.: Using social network analysis to support collective decision-making processes. International Journal of Decision Support System Technology, 3(2), pp. 15–31, 2011.CrossRefGoogle Scholar
  51. 134.
    Soto, R., Robles-Baldenegro, M.E., López, V.: MQDM: An iterative fuzzy method for group decision making in structured social networks. International Journal of Intelligent Systems, 32, pp. 17–30, 2017.CrossRefGoogle Scholar
  52. 135.
    Srdjevic, B.: Linking analytic hierarchy process and social choice methods to support group decision-making in water management. Decision Support Systems, 42, pp. 2261–2273, 2007.CrossRefGoogle Scholar
  53. 136.
    Stamatis, .D.H.: Failure mode and effect analysis: FMEA from theory to execution (2nd Ed). American Society for Quality Press, 2003.Google Scholar
  54. 138.
    Tapia-Rosero, A., De Tré, G.: Evaluating relevant opinions within a large group. Procs. International Conference on Fuzzy Computation Theory and Applications (FCTA-2014), pp. 76–86, 2014.Google Scholar
  55. 139.
    Tapia-Rosero, A., Bronselaer, A., De Tré, G.: A method based on shape-similarity for detecting similar opinions in group decision-making. Information Sciences, 258, pp. 291–311, 2014.CrossRefGoogle Scholar
  56. 140.
    Tapia-Rosero, A., De Mol, R., De Tré, G.: Handling uncertainty degrees in the evaluation of relevant opinions within a large group. In J.J. Merelo et al. (Eds.), Computational Intelligence, Studies in Computational Intelligence, 620, Springer, 283–299, 2015.Google Scholar
  57. 141.
    Tapia-Rosero, A.: Handling a Large Number of Preferences in a Multi-Level Decision-Making Process. PhD Thesis, Ghent University (Belgium), 2016.Google Scholar
  58. 142.
    Tapia-Rosero, A., Bronselaer, A., De Mol, R., De Tré, G.: Fusion of preferences from different perspectives in a decision-making context. Information fusion, 29, pp. 120–131, 2016.CrossRefGoogle Scholar
  59. 147.
    Ureña, R., Chiclana, F., Morente-Molinera, J.A., Herrera-Viedma, E.: Managing incomplete preference relations in decision making: A review and future trends. Information Sciences 302, pp. 14–32, 2015.MathSciNetCrossRefGoogle Scholar
  60. 149.
    Wang, J.Q.: Multi-criteria large-group linguistic decision-making approach with incomplete certain information. Procs. Chinese Control and Decision Conference, 2009. CCDC ’09, 2009.Google Scholar
  61. 151.
    Wu, J., Chiclana, F., Herrera-Viedma, E.: Trust based consensus model for social network in an incomplete linguistic information context. Applied Soft Computing, 35, pp. 827–839, 2015.CrossRefGoogle Scholar
  62. 152.
    Wu, T., Liu, X.W.: An interval type-2 fuzzy clustering solution for large-scale multiple-criteria group decision-making problems. Knowledge-based Systems, 144, pp. 118–127, 2016.CrossRefGoogle Scholar
  63. 153.
    Wu, T., Liu, X., Qin, J.: A linguistic solution for double large-scale group decision-making in E-commerce. Computers & Industrial Engineering, 116, pp. 97–112, 2018.CrossRefGoogle Scholar
  64. 154.
    Wu, T., Liu, X., Liu, F.: An interval type-2 fuzzy TOPSIS model for large scale group decision making problems with social network information. Information Sciences, 42, pp. 392–410, 2018.MathSciNetCrossRefGoogle Scholar
  65. 155.
    Wu, Z., Xu, J.: A consensus model for large-scale group decision making with hesitant fuzzy information and changeable clusters. Information Fusion, 41, pp. 217–231, 2018.CrossRefGoogle Scholar
  66. 158.
    Xiang, L.: Energy network dispatch optimization under emergency of local energy shortage with web tool for automatic large group decision-making. Energy, 120, pp. 740–750, 2017.CrossRefGoogle Scholar
  67. 159.
    Xu, X.H., Chen, X., Wang, H.: A kind or large group decision making method on the utility value preference information of decision member. Procs. 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008. WiCOM ’08, 2008.Google Scholar
  68. 161.
    Xu, X.H., Ahn, J., Chen, X., Zhou, Y.: Conflict measure model for large group decision based on interval intuitionistic trapezoidal fuzzy number and its application. Journal of Systems Science and Systems Engineering, 22(4), pp. 487–498, 2013.CrossRefGoogle Scholar
  69. 162.
    Xu, X.H., Liang, D., Chen, X., Zhou, Y.: A risk elimination coordination method for large group decision-making in natural disaster emergencies. Human and Ecological Risk Assessments: An International Journal, 21(5), pp. 1314–1325, 2014.CrossRefGoogle Scholar
  70. 163.
    Xu, X.H., Cai, C., Chen, X., Zhou, Y.: A multi-attribute large group emergency decision making method based on group preference consistency of generalized interval-valued trapezoidal fuzzy numbers. Journal of Systems Science and Systems Engineering, 24(2), pp. 211–228, 2015.CrossRefGoogle Scholar
  71. 164.
    Xu, X.H., Zhong, X.Y., Chen, X.H., Zhou, Y.J.: A dynamical consensus method based on exit-delegation mechanism for large group emergency decision making. Knowledge-based Systems, 86, pp. 237–249, 2015.CrossRefGoogle Scholar
  72. 165.
    Xu, X.H., Du, Z.J., Chen, X.H.: Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions. Decision Support Systems, 79, pp. 150–160, 2015.CrossRefGoogle Scholar
  73. 166.
    Xu, X.H., Wang, B., Zhou, Y.: A method based on trust model for large group decision-making with incomplete information. Journal of Intelligent & Fuzzy Systems, 30(6), pp. 3551–3565, 2016.CrossRefGoogle Scholar
  74. 167.
    Xu, X.H., Sun, Q., Pan, B., Liu, B.: Two-layer weight large group decision-making method based on multi-granular attributes. Journal of Intelligent and Fuzzy Systems, 33, pp. 1797–1807, 2017.CrossRefGoogle Scholar
  75. 168.
    Xu, Y., Wen, X., Zhang, W.: A two-stage consensus method for large-scale multi-attribute group decision making with an application to earthquake shelter selection. Computers & Industrial Engineering, 116, pp. 113–129, 2018.CrossRefGoogle Scholar
  76. 169.
    Xue, B., Xu, H.: A Whole Life Cycle Group Decision-Making Framework for Sustainability Evaluation of Major Infrastructure Projects. In K.W. Chau et al. (Eds.): Procs. 21st International Symposium on Advancement of Construction Management and Real Estate, pp. 129–141, Springer, 2018.Google Scholar
  77. 171.
    Yager, R., Rybalov, A.: Uninorm aggregation operators. Fuzzy Sets and Systems. 80, pp. 111–120, 1996.MathSciNetCrossRefGoogle Scholar
  78. 172.
    Yager, R., Filev, D.: Induced Ordered Weighted Averaging Operators. IEEE Transactions on Systems, Man and Cybernetics, 29, pp. 141–150, 1999.CrossRefGoogle Scholar
  79. 173.
    Yager, R.: Penalizing strategic preference manipulation in multi-agent decision making. IEEE Transactions on Fuzzy Systems, 9(3), pp. 393–403, 2001.MathSciNetCrossRefGoogle Scholar
  80. 175.
    Yu, W., Zhang, Z., Zhong, Q.Y.: A TODIM-Based Approach to Large-Scale Group Decision Making with Multi-Granular Unbalanced Linguistic Information. Procs. 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017.Google Scholar
  81. 176.
    Zadeh, L.A.: Fuzzy sets. Information and Control, 8(3), pp. 338–353. 1965.MathSciNetCrossRefGoogle Scholar
  82. 181.
    Zadeh, L.A.: Fuzzy logic = computing with words. IEEE Transactions on Fuzzy Systems, 4(2), pp. 103–111, 1996.CrossRefGoogle Scholar
  83. 182.
    Zahir, S.: Clusters in a group: decision making in the vector space formulation of the analytics hierarchy process. European Journal of Operational Research, 112, pp. 620–634, 1999.CrossRefGoogle Scholar
  84. 185.
    Zhang, F., Ignatius, J., Lim, C.P., Goh, M.: A two-stage dynamic group decision making method for processing ordinal information. Knowledge-based Systems, 70, pp. 189–202, 2014.CrossRefGoogle Scholar
  85. 186.
    Zhang, G., Dong, Y., Xu, Y.: Consistency and consensus measures for linguistic preference relations based on distribution assessments. Information Fusion, 17, pp. 46–55, 2014.CrossRefGoogle Scholar
  86. 187.
    Zhang, F., Ignatius, J., Zhao, Y., Lim, C.P., Ghasemi, M., Ng, P.S.: An improved consensus-based group decision making model with heterogeneous information. Applied Soft Computing, 35, pp. 850–863, 2015.CrossRefGoogle Scholar
  87. 188.
    Zhang, X.: A Novel Probabilistic Linguistic Approach for Large-Scale Group Decision Making with Incomplete Weight Information. International Journal of Fuzzy Systems, Aug. 2017, pp. 1–12, 2017.Google Scholar
  88. 189.
    Zhang, Z., Guo, C., Martínez, L.: Managing multigranular linguistic distribution assessments in large-scale multiattribute group decision making. IEEE Transactions on Systems, Man and Cybernetics: Systems, 47(11), pp. 3063–3076, 2017.CrossRefGoogle Scholar
  89. 190.
    Zhang, H., Dong, Y., Chen, X.: The 2-Rank Consensus Reaching Model in the Multigranular Linguistic Multiple-Attribute Group Decision-Making. IEEE Transactions on Systems, Man and Cybernetics: Systems, In Press. CrossRefGoogle Scholar
  90. 191.
    Zhang, H., Dong, Y., Herrera-Viedma, E.: Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions. IEEE Transactions on Fuzzy Systems, 26(2), pp. 884–898, 2018.CrossRefGoogle Scholar
  91. 192.
    Zhang, H., Palomares, I., Dong, Y., Wang, W.: Managing non-cooperative behaviors in consensus-based multiple attribute group decision making: An approach based on social network analysis. Knowledge-based Systems, In press. CrossRefGoogle Scholar
  92. 194.
    Zhu, J., Zhang, S., Chen, Y., Zhang, L.: A Hierarchical Clustering Approach Based on Three-Dimensional Gray Relational Analysis for Clustering a Large Group of Decision Makers with Double Information. Group Decision and Negotiation, 25, pp. 325–354, 2016.CrossRefGoogle Scholar
  93. 195.
    Zulueta, Y., Martínez-Moreno, J., Bello, R., Martínez, L.: A discrete time variable index for supporting dynamic multi-criteria decision making, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 22, pp. 1–22, 2014.CrossRefGoogle Scholar

Copyright information

© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Iván Palomares Carrascosa
    • 1
  1. 1.School of Computer Science (SCEEM)University of BristolBristolUK

Personalised recommendations