Advertisement

Introduction to Intelligent Decision Support Systems

  • Arturas KaklauskasEmail author
Chapter
  • 1.3k Downloads
Part of the Intelligent Systems Reference Library book series (ISRL, volume 81)

Abstract

This chapter presents definitions and descriptions of intelligent decision support systems (IDSSs) and analyzes the technology and AI methods, which serve as bases of the IDSS. Scholars have offered various definitions of IDSS. Every one of them accents that an intelligent decision support system is a DSS, which makes extensive use of artificial intelligence techniques. Artificial intelligence techniques can be utilized in all the components of IDSSs, such as in the data base, knowledge base, model base, user interface and the rest. Therefore this chapter deliberates the intelligent databases, hardware (sensors, iris camera hardware, hardware for fingerprint biometric identification, etc.) and computer human interfaces (gesture, intelligent user, motion tracking, voice and natural-language interfaces) in intelligent decision support systems.

Keywords

Recommender System Natural Language Processing Brain Computer Interface Intelligent Tutoring System Online Auction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Abel M, Silva LAL, De Ros LF, Mastella LS, Campbell JA, Novello T (2004) PetroGrapher: managing petrographic data and knowledge using an intelligent database application. Expert Syst Appl 26(1):9–18CrossRefGoogle Scholar
  2. Abraham A, Smith K, Jain R, Jain L (2007) Network and information security: a computational intelligence approach: special Issue of journal of network and computer applications. J Netw Comp Appl 30(1):1–3Google Scholar
  3. Akoumianakis D, Savidis A, Stephanidis C (2000) Encapsulating intelligent interactive behaviour in unified user interface artefacts. Interact Comput 12:383–408CrossRefGoogle Scholar
  4. Alavi M, Joachimsthaler E (1992) Revisiting DSS implementation research: a meta-analysis of the literature and suggestions for researchers. MIS Q 16(1):95–116CrossRefGoogle Scholar
  5. Attonaty J-M, Chatelin M-H, Garcia F (1999) Interactive simulation modeling in farm decision-making. Comput Electron Agric 22(2–3):157–170CrossRefGoogle Scholar
  6. Barranco CD, Campaña JR, Medina JM (2008) A Bimage-tree based indexing technique for fuzzy numerical data. Fuzzy Sets Syst 159(12):1431–1449CrossRefzbMATHGoogle Scholar
  7. Bostan-Korpeoglu B, Yazici A (2007) A fuzzy Petri net model for intelligent databases. Data Knowl Eng 62(2):219–247CrossRefGoogle Scholar
  8. Brown J (2008) Indexing infectious disease information with an intelligent database. Int J Infect Dis 12(1):e190–e191CrossRefGoogle Scholar
  9. Burstein F, Carlsson S (2008) Decision support through knowledge management. In: Burstein F, Holsapple CW (eds) Handbook on decision support systems 1: basic themes. Springer-Verlag, Berlin, pp 103–120CrossRefGoogle Scholar
  10. Canny J (2006) The future of human-computer interaction. Queue HCI 4(6):24–32CrossRefGoogle Scholar
  11. Chablo A (1994) Potential applications of artificial intelligence in telecommunications. Technovation 14(7):431–435CrossRefGoogle Scholar
  12. Chaitanya CS (2013) Designing and evaluating an interface for the composition of vibro-tactile patterns using gestures. Theses and dissertations, Ryerson UniversityGoogle Scholar
  13. Chrisley R (2008) Philosophical foundations of artificial consciousness. Artif Intell Med 44(2):119–137CrossRefGoogle Scholar
  14. Conati C, Merten C (2007) Eye-tracking for user modeling in exploratory learning environments: an empirical evaluation. Knowl-Based Syst 20(6):557–574CrossRefGoogle Scholar
  15. Doan A, Halevy A, Ives Z (2012) Ontologies and knowledge representation. In: Principles of data integration. Morgan Kaufmann, pp 325–344Google Scholar
  16. Domingos P, Lowd D (2009) Markov logic: an interface Layer for artificial intelligent. Morgan and Claypool Publishers, San RafaelGoogle Scholar
  17. Doukas H, Patlitzianas KD, Iatropoulos K, Psarras J (2007) Intelligent building energy management system using rule sets. Build Environ 42(10):3562–3569CrossRefGoogle Scholar
  18. Ehlert P (2003) Intelligent user interfaces. In: Introduction and survey. Research report DKS03-01/ICE 01Google Scholar
  19. Foehrenbach S, König WA, Gerken J, Reiterer H (2009) Tactile feedback enhanced hand gesture interaction at large, high-resolution displays. J Vis Lang Comput 20(5):341–351CrossRefGoogle Scholar
  20. Frati V, Prattichizzo D (2011) Using kinect for hand tracking and rendering in wearable haptics. In: IEEE world haptics conference, Istanbul, Turkey, 21–24 June 2011, pp 317–321Google Scholar
  21. Gajzler M (2010) Text and data mining techniques in aspect of knowledge acquisition for decision support system in construction industry. Technol Econ Dev Econ 16(2):219–232CrossRefGoogle Scholar
  22. Gajzler M (2013) The support of building management in the aspect of technical maintenance. Procedia Eng 54:615–624CrossRefGoogle Scholar
  23. Gao S, Wang H, Xu D, Wang Y (2007) An intelligent agent-assisted decision support system for family financial planning. Decis Support Syst 44(1):60–78CrossRefMathSciNetGoogle Scholar
  24. Garay-Vega L, Pradhan AK, Weinberg G, Schmidt-Nielsen B, Harsham B, Shen Y, Divekar G, Romoser M, Knodler M, Fisher DL (2010) Evaluation of different speech and touch interfaces to in-vehicle music retrieval systems. Accid Anal Prev 42(3):913–920CrossRefGoogle Scholar
  25. García-Cascales MS, Lamata MT (2007) Solving a decision problem with linguistic information. Pattern Recogn Lett 28(16):2284–2294CrossRefGoogle Scholar
  26. Gupta JND, Forgionne GA, Mora MT (eds) (2006) Intelligent decision-making support systems: foundations, applications and challenges. Springer, BerlinGoogle Scholar
  27. Håkansson A (2013) AIC—an AI-system for combination of senses. Procedia Comput Sci 22:40–49CrossRefGoogle Scholar
  28. Hartmann M (2010) Context-aware Intelligent user interfaces for supporting system use. Dissertation, Technischen Universität DarmstadtGoogle Scholar
  29. Hijikata Y, Ohno H, Kusumura Y, Nishida S (2007) Social summarization of text feedback for online auctions and interactive presentation of the summary. Knowl-Based Syst 20(6):527–541CrossRefGoogle Scholar
  30. Holsapple C (1977) Framework for a generalized intelligent decision support system. Dissertation, Purdue UniversityGoogle Scholar
  31. Holsapple C, Whinston A (1987) Business expert systems. McGraw-Hill, New YorkGoogle Scholar
  32. Hopgood AA (2005) The state of artificial intelligence. Adv Comput 65:1–75CrossRefGoogle Scholar
  33. Hwang G-J (2003) A conceptual map model for developing intelligent tutoring systems. Comput Educ 40:217–235CrossRefGoogle Scholar
  34. Jain LC, Chen Z (2003) Industry, artificial intelligence in encyclopedia of information systems, pp 583–597Google Scholar
  35. Järvensivu M, Juuso E, Ahava O (2001) Intelligent control of a rotary kiln fired with producer gas generated from biomass. Eng Appl Artif Intell 14(5):629–653CrossRefGoogle Scholar
  36. Jelassi MT (1986) MCDM: from “stand-alone” methods to integrated and Intelligent DSS. In: Sawaragi Y, Inoue K, Nakayama H (eds) Toward interactive and intelligent decision support systems. In: 7th international conference on multiple criteria decision making, Kyoto, 18–22 Aug 1986. Lecture notes in economics and mathematical systems, vol 286. Springer-Verlag, Berlin, pp 90–99Google Scholar
  37. Jiang F, Gao W, Yao H, Zhao D, Chen X (2008) Effort analysis in signer-independent sign gestures. J Exp Theor Artif Intell 20(2):133–152CrossRefGoogle Scholar
  38. Johnson L, Smith R, Willis H, Levine A, Haywood K (2011) The 2011 horizon report. The New Media Consortium, AustinGoogle Scholar
  39. Josephina MP, Nkambou R (2002) Hierarchical representation and evaluation of the student in an intelligent tutoring system. In: Cerri AS, Gouarderes G, Paraguacu F (eds) Proceedings of the sixth international conference on intelligent tutoring systems—ITS 2002, vol 2363. LNCS, Springer, Berlin, pp 708–717Google Scholar
  40. Jothiprakash V, Magar RB (2012) Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data. J Hydrol 450–451:293–307CrossRefGoogle Scholar
  41. Kaklauskas A, Zavadskas E, Ditkevicius R (2006) an intelligent tutoring system for construction and real estate management master degree studies. In: Luo Y (ed) CDVE 2006, LNCS 4101. Springer, Heidelberg, pp 174–181Google Scholar
  42. Kaklauskas A, Zavadskas E, Babenskas E, Seniut M, Vlasenko A, Plakys V (2007) Intelligent library and tutoring system for brita in the PuBs project. In: Luo Y (ed) CDVE: 2007, LNCS 4674. Springer, Heidelberg, pp 157–166Google Scholar
  43. Kaklauskas A, Zavadskas EK, Pruskus V, Vlasenko A, Seniut M, Kaklauskas G, Matuliauskaite A, Gribniak V (2010) Biometric and intelligent self-assessment of student progress system. Comput Educ 55(2):821–833CrossRefGoogle Scholar
  44. Kaklauskas A, Zavadskas EK, Seniut M, Dzemyda G, Stankevic V, Simkevičius C, Stankevic T, Paliskiene R, Matuliauskaite A, Kildiene S, Bartkiene L, Ivanikovas S, Gribniak V (2011) Web-based biometric computer mouse advisory system to analyze a user’s emotions and work productivity. Eng Appl Artif Intell 24(6):928–945CrossRefGoogle Scholar
  45. Kaklauskas A, Rute J, Zavadskas EK, Daniunas A, Pruskus V, Bivainis J, Gudauskas R, Plakys V (2012) Passive house model for quantitative and qualitative analyses and its intelligent system. Energy Build 50:7–18CrossRefGoogle Scholar
  46. Kaklauskas A, Kutinis M, Kovachev L, Petkov P, Bartkiene L, Jackute I (2013a) Housing health and safety decision support system with augmented reality. In: Howlett et al (eds) IMED: innovation in medicine and healthcare, pp 131–143Google Scholar
  47. Kaklauskas A, Zavadskas EK, Seniut M, Stankevic V, Raistenskis J, Simkevičius C, Stankevic T, Matuliauskaite A, Bartkiene L, Zemeckyte L, Paliskiene R, Cerkauskiene R, Gribniak V (2013b) Recommender system to analyze student’s academic performance. Expert Syst Appl 40(15):6150–6165CrossRefGoogle Scholar
  48. Kaklauskas A, Vlasenko A, Raudonis V, Zavadskas EK, Gudauskas R, Seniut M, Juozapaitis A, Jackute I, Kanapeckiene L, Rimkuviene S, Kaklauskas G (2013c) Student progress assessment with the help of an intelligent pupil analysis system. Eng Appl Artif Intell 26(1):35–50CrossRefGoogle Scholar
  49. Kim BH, Kim M, Jo S (2014) Quadcopter flight control using a low-cost hybrid interface with EEG-based classification and eye tracking. Comput Biol Med 51:82–92CrossRefGoogle Scholar
  50. Kumar S, Sekmen A (2008) Single robot—multiple human interaction via intelligent user interfaces. Knowl-Based Syst 21(6):458–465CrossRefGoogle Scholar
  51. Lee EC, Woo JC, Kim JH, Whang M, Park KR (2010) A brain–computer interface method combined with eye tracking for 3D interaction. J Neurosci Methods 190(2):289–298CrossRefGoogle Scholar
  52. Lee CKH, Choy KL, Law KMY, Ho GTS (2014) Application of intelligent data management in resource allocation for effective operation of manufacturing systems. J Manuf Syst 33(3):412–422CrossRefGoogle Scholar
  53. Levitt TS (1986) Model-based probabilistic situation inference in hierarchical hypothesis spaces. Mach Intell Pattern Recognit 4:347–356CrossRefGoogle Scholar
  54. Lieberman H, Espinosa J (2007) A goal-oriented interface to consumer electronics using planning and commonsense reasoning. Knowl-Based Syst 20(6):592–606CrossRefGoogle Scholar
  55. Lu J, Ruan D, Zhang G (2010) A special issue on intelligent decision support and warning systems. Knowl-Based Syst 23(1):1–2CrossRefGoogle Scholar
  56. Magoulas GD, Papanikolaou KA, Grigoriadou M (2001) Neuro fuzzy synergism for planning the content in a web-based course. Informatica 25:39–48zbMATHGoogle Scholar
  57. Marín N, Pons O (2008) Advances in intelligent databases and information systems. Fuzzy Sets Syst 159(12):1429–1430CrossRefGoogle Scholar
  58. Matsatsinis NF, Siskos Y (1999) MARKEX: an intelligent decision support system for product development decisions. Eur J Oper Res 113(2):336–354CrossRefzbMATHGoogle Scholar
  59. McCarthy J (2007) What is artificial intelligence? Stanford University. http://www-formal.stanford.edu/jmc/whatisai/node2.html. Accessed 5 Feb 2014
  60. Medsker LR (1996) Microcomputer applications of hybrid intelligent systems. J Network Comput Appl 19(2):213–234CrossRefGoogle Scholar
  61. Morales R, Blanco I, Pons O, Rodríguez J (2008) GDB: a tool to build deductive rules using a fuzzy relational database with scientific data. Fuzzy Sets Syst 159(12):1577–1596CrossRefGoogle Scholar
  62. Murphy F, Stohr E (1986) An intelligent support for formulating linear programming. Decis Support Syst 2:1CrossRefGoogle Scholar
  63. Nemati HR, Steiger DM, Iyer LS, Herschel RT (2002) Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decis Support Syst 33(2):143–161CrossRefGoogle Scholar
  64. Nihalani N, Silakari S, Motwani M (2009) Integration of artificial intelligence and database management system: an inventive approach for intelligent databases. In: Paper presented at 2009 1st international conference on computational intelligence, communication systems and networks, CICSYN ’09, pp 35–40, 23–25 July 2009Google Scholar
  65. O’Leary DE (2008) Decision Support System Evolution. In: Burstein F, Holsapple C (eds) Handbook on decision support systems. Springer-Verlag, Heidelberg, pp 345–370CrossRefGoogle Scholar
  66. Papamichail KN, French S (2005) Design and evaluation of an intelligent decision support system for nuclear emergencies. Decis Support Syst 41(1):84–111CrossRefGoogle Scholar
  67. Paris C, Sidner CL (2007) Introduction to the KBS special issue on intelligent user interfaces. Know-Based Syst 20(6):509–510CrossRefGoogle Scholar
  68. Phillips-Wren G, Mora M, Forgionne GA, Gupta JND (2009) An integrative evaluation framework for intelligent decision support systems. Eur J Oper Res 195(3):642–652CrossRefzbMATHGoogle Scholar
  69. Pomerol JC, Roy B, Rosenthal-Sabroux C, Saad A (1995) An “Intelligent” DSS for the multicriteria evaluation of railway timetables. Found Comput Decis Sci 20(3):219–238zbMATHGoogle Scholar
  70. Prentzas J, Hatzilygeroudis I, Garofalakis J (2002) A web-based intelligent tutoring system using hybrid rules as its representational basis. In: Cerri AS, Gouarderes G (eds) Sixth international conference, ITS-2002, vol 2363. LNCS, Springer, BerlinGoogle Scholar
  71. Pu P, Chen L (2007) Trust-inspiring explanation interfaces for recommender systems. Knowl-Based Syst 20(6):542–556CrossRefGoogle Scholar
  72. Quintero A, Konaré D, Pierre S (2005) Prototyping an intelligent decision support system for improving urban infrastructures management. Eur J Oper Res 162(3):654–672CrossRefzbMATHGoogle Scholar
  73. Regazzoni D, de Vecchi G, Rizzi C (2014) RGB cams vs RGB-D sensors: low cost motion capture technologies performances and limitations. J Manuf Syst doi:  10.1016/j.jmsy.2014.07.011
  74. Rizzoli AE, Young WJ (1997) Delivering environmental decision support systems: software tools and techniques. Environ Model Softw 12(2–3):237–249CrossRefGoogle Scholar
  75. Sarma VVS (1994) Decision-making in complex-systems. Syst Pract 7(4):399–407CrossRefMathSciNetGoogle Scholar
  76. Saunders JH (2000) A primer on artificial intelligence technologies. http://users.erols.com/jsaunders/papers/aitechniques.htm. Accessed 12 Feb 2014
  77. Shen LY, Ochoa JJ, Zhang X, Yi P (2013) Experience mining for decision making on implementing sustainable urbanization—an innovative approach. Autom Constr 29:40–49CrossRefGoogle Scholar
  78. Simic G, Devedzic V (2003) Building an intelligent system using modern internet technologies. Expert Syst Appl 25:231–246CrossRefGoogle Scholar
  79. Şişman-Yılmaz NA, Alpaslan FN, Jain L (2004) ANFISunfoldedintime for multivariate time series forecasting. Neurocomputing 61:139–168Google Scholar
  80. Slowinski R, Stefanowski J (1992) “RoughDAS” and “Rough-Class” software implementations of the rough set approach. In: Slowinski R (ed) Intelligent decision support. Handbook of applications and advances of the rough sets theory. Kluwer Academic Publishers, Dordrecht, pp 445–456Google Scholar
  81. Sun M, Chai JY (2007) Discourse processing for context question answering based on linguistic knowledge. Knowl-Based Syst 20(6):511–526CrossRefGoogle Scholar
  82. Teng JTC, Mirani R, Sinha A (1988) A unified architecture for intelligent DSS. In: Proceedings of the 21st annual Hawaii international conference on decision support and knowledge based systems track, Hawaii, pp 286–294Google Scholar
  83. Turban E, Aronson J (2001) Decision support and intelligent systems. Prentice-Hall International, Upper Saddle RiverGoogle Scholar
  84. Turban E, Watkins P (1986) Integrating expert systems and decision support systems. MIS Q 10(2):121–136CrossRefGoogle Scholar
  85. Turban E, Aronson JE, Liang T-P (2005) Decision support systems and intelligent systems, 7th edn. Prentice-Hall, Inc, Upper Saddle RiverGoogle Scholar
  86. Turban E, Aronson JE, Liang TP, Sharda R (2007) Decision support systems and intelligent systems, 8th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  87. Wang HQ (1997) Intelligent agent assisted decision support systems: integration of knowledge discovery, knowledge analysis, and group decision support. Expert Syst Appl 12(3):323–335CrossRefGoogle Scholar
  88. Wan S, Lei TC (2009) A knowledge-based decision support system to analyze the debris-flow problems at Chen-Yu-Lan River, Taiwan. Knowl-Based Syst 22(8):580–588CrossRefGoogle Scholar
  89. Wood SD, Zaientz J, Beard J, Frederiksen R, Lisse S, Crossman J, Huber M (2004) An intelligent interface-agent framework for supervisory command and control. In: 2004 command and control research and technology symposium, The Power of Information Age Concepts and Technologies, Arlington, VirginiaGoogle Scholar
  90. Yang Y, Tan W, Li T, Ruan D (2012) Consensus clustering based on constrained self-organizing map and improved Cop-Kmeans ensemble in intelligent decision support systems. Knowl-Based Syst 32:101–115CrossRefGoogle Scholar
  91. Zhang Z (2012) Microsoft Kinect sensor and its effect. IEEE Multimedia 19(2):4–10CrossRefGoogle Scholar
  92. Zhang G, Xu Y, Li T (2012) A special issue on new trends in Intelligent decision support systems. Knowl-Based Syst 32:1–2CrossRefzbMATHGoogle Scholar
  93. Zhendong VK (2001) Bayesian student modelling, user interfaces and feedback: a sensitivity analysis. Int J Artif Intell Educ 12(2):155–184Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Vilnius Gediminas Technical UniversityVilniusLithuania

Personalised recommendations