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Journal articles on the topic 'Expert systems (computer science)'

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Published: 4 June 2021

Last updated: 30 July 2024

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1

Matsuzaka, Yasunari, and Ryu Yashiro. "AI-Based Computer Vision Techniques and Expert Systems." AI 4, no. 1 (February 23, 2023): 289–302. http://dx.doi.org/10.3390/ai4010013.

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Computer vision is a branch of computer science that studies how computers can ‘see’. It is a field that provides significant value for advancements in academia and artificial intelligence by processing images captured with a camera. In other words, the purpose of computer vision is to impart computers with the functions of human eyes and realise ‘vision’ among computers. Deep learning is a method of realising computer vision using image recognition and object detection technologies. Since its emergence, computer vision has evolved rapidly with the development of deep learning and has significantly improved image recognition accuracy. Moreover, an expert system can imitate and reproduce the flow of reasoning and decision making executed in human experts’ brains to derive optimal solutions. Machine learning, including deep learning, has made it possible to ‘acquire the tacit knowledge of experts’, which was not previously achievable with conventional expert systems. Machine learning ‘systematises tacit knowledge’ based on big data and measures phenomena from multiple angles and in large quantities. In this review, we discuss some knowledge-based computer vision techniques that employ deep learning.

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2

Cooper, Philip. "Expert systems in management science." Future Generation Computer Systems 2, no. 4 (December 1986): 217–23. http://dx.doi.org/10.1016/0167-739x(86)90021-x.

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3

Jones, R. P. "Expert systems." International Review of Law, Computers & Technology 2, no. 1 (January 1986): 142–44. http://dx.doi.org/10.1080/13600869.1986.9966241.

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4

Miller, CDF. "Expert systems." Data Processing 27, no. 6 (July 1985): 49. http://dx.doi.org/10.1016/0011-684x(85)90281-3.

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5

Upchurch, E. T., K. S. Raman, and K. Ranai. "Designing expert systems for modeling complex computer systems." ISA Transactions 28, no. 1 (January 1989): 27–29. http://dx.doi.org/10.1016/0019-0578(89)90053-0.

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6

El-Najdawi, M. K., and Anthony C. Stylianou. "Expert support systems." Communications of the ACM 36, no. 12 (December 1993): 55. http://dx.doi.org/10.1145/163298.163306.

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7

Gallant, Stephen I. "Connectionist expert systems." Communications of the ACM 31, no. 2 (February 1988): 152–69. http://dx.doi.org/10.1145/42372.42377.

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8

Ruttkay, Z. "Expert systems in computer-aided design." Computer-Aided Design 21, no. 9 (November 1989): 596. http://dx.doi.org/10.1016/0010-4485(89)90022-5.

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9

Lirov, Yuval. "Computer-aided software engineering of expert systems." Expert Systems with Applications 2, no. 4 (January 1991): 333–43. http://dx.doi.org/10.1016/0957-4174(91)90039-h.

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10

Grindley, Kit. "Applying expert principles to computer systems development." Data Processing 28, no. 1 (January 1986): 10–14. http://dx.doi.org/10.1016/0011-684x(86)90183-8.

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11

Jones, Russell. "Commercial expert systems." Data Processing 28, no. 3 (April 1986): 115–19. http://dx.doi.org/10.1016/0011-684x(86)90002-x.

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12

MacCallum, K. J. "Expert systems '85." Artificial Intelligence in Engineering 1, no. 1 (July 1986): 58. http://dx.doi.org/10.1016/0954-1810(86)90036-1.

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13

Sucharov, Lance. "Expert systems 87." Artificial Intelligence in Engineering 5, no. 4 (October 1990): 226. http://dx.doi.org/10.1016/0954-1810(90)90029-4.

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14

Jeapes, Ben. "Vale Expert Systems." Electronic Library 14, no. 3 (March 1996): 195–96. http://dx.doi.org/10.1108/eb045466.

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15

Prantosh Kr. Pau, C., R. Senthamarai, K. S. Shivraj, D. Chatterjee, and B. Karn. "Artificial Intelligence and Expert Systems: Its Emerging Interaction and Importance in Information Science – An overview." Asian Journal of Electrical Sciences 1, no. 2 (November 5, 2012): 6–10. http://dx.doi.org/10.51983/ajes-2012.1.2.1684.

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This paper mainly deals with overview of artificial intelligence and Expert System. Artificial Intelligence primarily responsible for developing computer programs which are able to read, speak, and understand as like man. Other hand Expert System refers to expert System needed for advance decision and intelligence robotics application. Expert System can communicate with user in their natural language and processes the capacity to catch to the individual desire. Here in this paper role of Artificial Intelligence and Expert System elaborate briefly, where as application of these computer techniques get most priority. We also discuss the need of Artificial Intelligence and emerging Expert System in the working and academic field of information Science.

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16

Rosenman, Michael A., John S. Gero, Peter J. Hutchinson, and Rivka Oxman. "Expert systems applications in computer-aided design." Computer-Aided Design 18, no. 10 (December 1986): 546–51. http://dx.doi.org/10.1016/0010-4485(86)90043-6.

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17

Rosenman, Michael A., John S. Gero, Peter J. Hutchinson, and Rivka Oxman. "Expert systems applications in computer-aided design." Computer-Aided Design 18, no. 7 (September 1986): 392–93. http://dx.doi.org/10.1016/0010-4485(86)90248-4.

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18

Ullmann, Julian. "Managing expert systems." Information and Software Technology 30, no. 5 (June 1988): 315. http://dx.doi.org/10.1016/0950-5849(88)90027-4.

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19

Li, G. "Developing expert systems." Information and Software Technology 32, no. 4 (May 1990): 319. http://dx.doi.org/10.1016/0950-5849(90)90081-2.

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20

Prakash, N. "Expert database systems." Information and Software Technology 32, no. 8 (October 1990): 572–73. http://dx.doi.org/10.1016/0950-5849(90)90153-i.

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21

Li, G. "Expert systems introduced." Information and Software Technology 33, no. 6 (July 1991): 462–63. http://dx.doi.org/10.1016/0950-5849(91)90084-o.

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22

Tanik, MM. "Creating expert systems." Information and Software Technology 33, no. 8 (October 1991): 607. http://dx.doi.org/10.1016/0950-5849(91)90127-w.

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23

Whittington, RP. "Expert database systems." Information and Software Technology 33, no. 4 (May 1991): 301. http://dx.doi.org/10.1016/0950-5849(91)90155-5.

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24

d'Agapeyeff, A. "What are Expert Systems?" Journal of Computer Assisted Learning 2, no. 1 (March 1986): 28–36. http://dx.doi.org/10.1111/j.1365-2729.1986.tb00061.x.

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25

SHAHABUDDIN, SYED. "Expert systems and forecasting." International Journal of Systems Science 21, no. 10 (October 1990): 1997–2004. http://dx.doi.org/10.1080/00207729008910519.

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26

Wang, Paul P., and Keith M. Sullivan. "Medical expert systems." Information Sciences 162, no. 2 (May 2004): 63–64. http://dx.doi.org/10.1016/j.ins.2004.03.001.

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27

Dym, Clive L. "EXPERT SYSTEMS: New approaches to computer-aided engineering." Engineering with Computers 1, no. 1 (March 1985): 9–25. http://dx.doi.org/10.1007/bf01200335.

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28

Kelly, Peter. "Expert systems using shells." Data Processing 28, no. 3 (April 1986): 139–40. http://dx.doi.org/10.1016/0011-684x(86)90005-5.

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29

Roberts, H. J. "Expert Systems Clubs: Design Methods." Computer Journal 33, no. 6 (June 1, 1990): 556–61. http://dx.doi.org/10.1093/comjnl/33.6.556.

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30

Silverman, Barry G. "Survey of expert critiquing systems." Communications of the ACM 35, no. 4 (April 1992): 106–27. http://dx.doi.org/10.1145/129852.129861.

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31

Bobrow, D. G., S. Mittal, and M. J. Stefik. "Expert systems: perils and promise." Communications of the ACM 29, no. 9 (September 1986): 880–94. http://dx.doi.org/10.1145/6592.6597.

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32

Mercy, Andy. "Devoping expert CAD systems." Artificial Intelligence in Engineering 1, no. 1 (July 1986): 63. http://dx.doi.org/10.1016/0954-1810(86)90045-2.

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33

Carter, Ian M. "Application of expert systems." Artificial Intelligence in Engineering 4, no. 1 (January 1989): 54. http://dx.doi.org/10.1016/0954-1810(89)90025-3.

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34

Seifoddini, Hamid. "Machine grouping — Expert systems." Computers & Industrial Engineering 15, no. 1-4 (January 1988): 210–16. http://dx.doi.org/10.1016/0360-8352(88)90088-5.

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35

P, DURAISAMY. "ARTIFICIAL INTELLIGENCE BASED EXPERT SYSTEMS: APPLICATIONS TO HORTICULTURE." Madras Agricultural Journal 83, February (1996): 98–101. http://dx.doi.org/10.29321/maj.10.a00978.

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Decreasing supporting resources and increasing complexity of horticultural crop production necessitate the new technologies be developed to transfer information to farmers as well as commercial producers. Expert systems, a sub area of artificial intelligence of computer science offer the possibility to implement horticultural knowledge into field practice in the form of computer programme in order to support the farmers in decision making at farm level. This paper provides an overview of the concept of expert system and examples of areas of horticultural applications of these systems are in use at present are also outlined. This paper further examines how expert system techniques are being used at present in problem solving and why someone in the field of horticulture might want to use them.

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36

Davies, B. J. "Expert systems." International Journal of Advanced Manufacturing Technology 2, no. 1 (February 1987): 1–2. http://dx.doi.org/10.1007/bf02601464.

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37

Gero, John. "Expert systems in CAD." Computer-Aided Design 17, no. 9 (November 1985): 396–98. http://dx.doi.org/10.1016/0010-4485(85)90286-6.

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38

Lee, Daniel T. "Expert Decision-support Systems for Decision-making." Journal of Information Technology 3, no. 2 (June 1988): 85–94. http://dx.doi.org/10.1177/026839628800300204.

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Computers have made tremendous contributions towards transactional processing. However, the highest pay-off the computer can make is not in transactional processing but in decision-making. Recently, expert systems have just begun to be used in the decision-making process. Individual technologies alone are inadequate for an effective decision support. The purpose of this paper is to investigate the related issues in decision support and to develop an expert decision support system (EDSS) for combining decision support systems and expert systems into a unified whole for decision support. The emphasis will be on developing a DSS/ES model which can be used to integrate the traditional DSS database and ES knowledge-base for building a user-friendly EDSS.

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39

Yoe Kwa, H., Johan van der Lei, and Jan A. Kors. "Expert systems integrated with information systems." Computer Methods and Programs in Biomedicine 25, no. 3 (November 1987): 327–32. http://dx.doi.org/10.1016/0169-2607(87)90091-5.

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40

Liebowitz, Jay. "Expert systems." Kybernetes 27, no. 2 (March 1998): 170–75. http://dx.doi.org/10.1108/03684929810205832.

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41

Silverman, Barry G. "Unifying Expert Systems and the Decision Sciences." Operations Research 42, no. 3 (June 1994): 393–413. http://dx.doi.org/10.1287/opre.42.3.393.

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42

de Jong, Lieuwe Sytse. "Engineering of expert systems." Information and Software Technology 30, no. 7 (September 1988): 418–25. http://dx.doi.org/10.1016/0950-5849(88)90038-9.

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43

Ullmann, Julian. "Expert systems for managers." Information and Software Technology 30, no. 2 (March 1988): 124. http://dx.doi.org/10.1016/0950-5849(88)90075-4.

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44

Tanik, M. M. "Research and development in expert systems V: Proceedings of Expert Systems' 88." Information and Software Technology 31, no. 8 (October 1989): 451. http://dx.doi.org/10.1016/0950-5849(89)90124-9.

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45

Gao, Shengxiang, Zhengtao Yu, Linbin Shi, Xin Yan, and Haixia Song. "A Method to Review Expert Recommendation Using Topic Relevance and Expert Relationship." International Journal of Cooperative Information Systems 27, no. 01 (March 2018): 1741004. http://dx.doi.org/10.1142/s0218843017410040.

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In the process of recommending review experts to projects, in order to effectively make use of the relevance among topics and the relationship among experts, a new method is proposed for review expert recommendation using topic relevance and expert relationship. In this method, firstly, the relevance among topics and the relationships among experts are used to respectively construct the Markov network of topics and the Markov network of experts. Next, the maximum topic clique is extracted from the topic Markov network and the maximum expert clique is extracted from the expert Markov network; then, with the information of the two maximum cliques, the relevance between experts and projects is calculated. After that, according to the descending order of the relevant degree, the candidates are ranked. Finally, the experts, who are the top N to projects, are recommended. The experiments on five domain datasets are made and the results show that the proposed method can improve the effect of review expert recommendation, and the F-value increases by an average of 5% than without considering the relevance among topics and the relationship among experts.

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46

Peyton, C. "An introduction to expert systems." Journal of Computer Assisted Learning 1, no. 1 (March 1985): 25–32. http://dx.doi.org/10.1111/j.1365-2729.1985.tb00005.x.

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47

Reynolds, C. F. "Introducing expert systems to pupils." Journal of Computer Assisted Learning 4, no. 2 (June 1988): 79–92. http://dx.doi.org/10.1111/j.1365-2729.1988.tb00268.x.

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48

Ruyle, Kim E. "Expert systems: They’re here now." TechTrends 34, no. 1 (January 1989): 41–43. http://dx.doi.org/10.1007/bf02771290.

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49

Jones, Russell. "European expert systems project for systems developers." Data Processing 28, no. 1 (January 1986): 15–17. http://dx.doi.org/10.1016/0011-684x(86)90184-x.

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50

McKinion, J. M., and H. E. Lemmon. "Expert systems for agriculture." Computers and Electronics in Agriculture 1, no. 1 (October 1985): 31–40. http://dx.doi.org/10.1016/0168-1699(85)90004-3.

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