• citations in SCIndeks: 0
  • citations in CrossRef:[1]
  • citations in Google Scholar:[]
  • visits in previous 30 days:4
  • full-text downloads in 30 days:4


article: 7 from 38  
Back back to result list
2015, vol. 17, iss. 2, pp. 123-137
Improving business helpdesk systems with intelligent search mechanisms
aTechnical College of Applied Studies in Kragujevac, Kragujevac
bUniveristy of Niš, Faculty of Economy
cVTSSS Zvecan
Modern information systems widely use intelligent tools for detection, recognition and prediction of new knowledge. The area of implementation of such systems is huge and there is almost no area of industry and services, where such systems are not represented. The aim of the development of such systems is to obtain such an information system in the future that will have full functionality with the ability to upgrade without the intervention of a software development team. The paper proposes an intelligent software solution as a part of the way toward the set ideal software solution. It will particularly highlight that the methodology by which the prototype of the proposed software solution was developed represents a valid basis for the development of software solutions for different areas and services.
Béchet, N., Chauché, J., Prince, V., Roche, M. (2014) How to combine text-mining methods to validate induced Verb-Object relations?. Computer Science and Information Systems, 11(1): 133-155
Cibran, M.A. (2007) Connecting high-level business ruleswith object-oriented applications: An approach using aspect-oriented programming and model-driven engineering. Uitgever VUBPRESS
Codington, S., Wilson, T.D. (1994) Information system strategies in the UK Insurance Industry. International Journal of Information Management, 14(3): 188-203
Daniels, H., van Dissel, H. (2002) Risk management based on expert rules and data-mining: A case study in insurance. in: ECIS 2002 - 6-8. June, Gdańsk, Poland
Medina-Santiago, A., Camas-Anzueto, J.L., Vazquez-Feijoo, J.A., Hernández-de, L.H.R., Mota-Grajales, R. (2014) Neural Control System in Obstacle Avoidance in Mobile Robots Using Ultrasonic Sensors. Journal of Applied Research and Technology, 12(1): 104-110
Nalepa, G., Bobek, S. (2014) Rule-based solution for context-aware reasoning on mobile devices. Computer Science and Information Systems, 11(1): 171-193
Rivera-Mejía, J., Léon-Rubio, A.G., Arzabala-Contreras, E. (2012) PID Based on a Single Artificial Neural Network Algorithm for Intelligent Sensors. Journal of Applied Research and Technology, 10(2):
Rodríguez-González, A., Torres-Niño, J., Domingo, J., Gomez-Berbis, M.J., Alor-Hernandez, G. (2012) AKNOBAS: A knowledge-based segmentation recommender system based on intelligent data mining techniques. Computer Science and Information Systems / ComSIS, vol. 9, br. 2, str. 713-740
SAS (2012) Combating insurance claims fraud: How to recognize and reduce opportunistic and organized claims fraud. in: SAS White Paper
Stankić, R., Milićević, V., Popović, M., Savić, Z. (2012) Contribution to intelligent system for automatic management of business rules development. TTEM, Vol. 7, 1
Torpey, D. (2011) Fraud in insurance on rise - survey 2010-2011. Ernst & Young
Yeremia (2013) Genetic algorithm and neural network for optical character recognition. Journal of Computer Science, 9(11): 1435-1442


article language: English
document type: Professional Paper
DOI: 10.5937/EkoPog1502123M
published in SCIndeks: 31/12/2019

Related records

No related records