ABSTRACT
A new recommendation framework that addresses the correct and quick resolution of incidents that occur within the complex systems of an enterprise is introduced here. It uses statistical learning to mediate problem solving by large-scale Resolution Service Networks (with nodes as technical expert groups) that collectively resolve the incidents logged as tickets. Within the enterprise a key challenge is to resolve the tickets arising from operational big data (1) to the customers' satisfaction, and (2) within a time constraint. That is, meet the service level (SL) goals. The challenge in meeting SL is the lack of a global understanding of the types of needed problem solving expertise. Consequently, this often leads to ticket misrouting to experts that are inappropriate for solving the next increment of the problem. The solution here proposes a general two-level classification framework to recommend a SL-efficient sequence of expert groups that jointly can resolve an incoming ticket. The experimental validation shows 34% accuracy improvement over existing locally applied generative models. Additionally, recommended sequences are above 96% likely to meet the enterprise SL goals, which reduces the SL violation rate by 29%. Recommendations are suppressed in the case of non-routine content which is automatically flagged for special attention by humans, since here the humans outperform statistical models.
- F. Cabitza and C. Simone. Computational coordination mechanisms: A tale of a struggle for flexibility. Computer Supported Cooperative Work (CSCW), 22(4-6):475--529, 2013. Google ScholarDigital Library
- E. Charniak. Statistical language learning. MIT press, 1996. Google ScholarDigital Library
- Y. Chen, S. Tao, X. Yan, N. Anerousis, and Q. Shao. Assessing expertise awareness in resolution networks. In Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on, pages 128--135. IEEE, 2010. Google ScholarDigital Library
- O. Dekel and O. Shamir. Multiclass-multilabel classification with more classes than examples. In International Conference on Artificial Intelligence and Statistics, pages 137--144, 2010.Google Scholar
- V. Kaptelinin and B. Nardi. Affordances in hci: toward a mediated action perspective. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 967--976. ACM, 2012. Google ScholarDigital Library
- D. J. MacKay. Information theory, inference and learning algorithms. Cambridge university press, 2003. Google ScholarDigital Library
- G. Miao, L. E. Moser, X. Yan, S. Tao, Y. Chen, and N. Anerousis. Generative models for ticket resolution in expert networks. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 733--742. ACM, 2010. Google ScholarDigital Library
- G. Miao, L. E. Moser, X. Yan, S. Tao, Y. Chen, and N. Anerousis. Reliable ticket routing in expert networks. In Reliable Knowledge Discovery, pages 127--147. Springer, 2012.Google ScholarCross Ref
- K. Moharreri, M. Ha, and R. H. Nehm. Evograder: an online formative assessment tool for automatically evaluating written evolutionary explanations. Evolution: Education and Outreach, 7(1):1--14, 2014.Google ScholarCross Ref
- D. Oppenheim, S. Bagheri, K. Ratakonda, and Y.-M. Che. Agility of enterprise operations across distributed organizations: A model of cross enterprise collaboration. In SRII Global Conference (SRII), 2011 Annual, pages 154--162. IEEE, 2011. Google ScholarDigital Library
- B. Orand and J. Villareal. Foundations of it service management with itil 2011: Itil foundation course in a book. c. August, 2011.Google Scholar
- J. Ramanathan, R. Ramnath, and S. Ramakrishnan. Achieving'handoff'traceability for complex systemimprovement. In Proceedings of the fifth annual IEEE international conference on Automation science and engineering, pages 641--646. IEEE Press, 2009. Google ScholarDigital Library
- J. D. Rennie, L. Shih, J. Teevan, D. R. Karger, et al. Tackling the poor assumptions of naive bayes text classifiers. In ICML, volume 3, pages 616--623. Washington DC), 2003.Google ScholarDigital Library
- Q. Shao, Y. Chen, S. Tao, X. Yan, and N. Anerousis. Efficient ticket routing by resolution sequence mining. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 605--613. ACM, 2008. Google ScholarDigital Library
- S. Srikant and V. Aggarwal. A system to grade computer programming skills using machine learning. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1887--1896. ACM, 2014. Google ScholarDigital Library
- H. Sun, M. Srivatsa, S. Tan, Y. Li, L. M. Kaplan, S. Tao, and X. Yan. Analyzing expert behaviors in collaborative networks. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1486--1495. ACM, 2014. Google ScholarDigital Library
- W. Van Der Aalst. Process mining: discovery, conformance and enhancement of business processes. Springer Science & Business Media, 2011. Google ScholarDigital Library
- W. M. Van der Aalst. Using process mining to bridge the gap between bi and bpm. IEEE Computer, 44(12):77--80, 2011. Google ScholarDigital Library
- L. Yu, S. Wang, and K. K. Lai. An intelligent agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring. European Journal of Operational Research, 195(3):942--959, 2009.Google ScholarCross Ref
Index Terms
Recommendations for Achieving Service Levels within Large-scale Resolution Service Networks
Recommendations
Text image super resolution using within-scale repetition of characters and strokes
In text images, there are some frequently used characters repeating more than others. Likewise, some characters have common strokes. This characteristic is used in this paper for machine-printed text-image super resolution. After segmenting the input ...
A text mining based approach for web service classification
Web services have evolved as a versatile and cost effective solution for exchanging dissimilar data between distributed applications. They have become a fundamental part of service oriented architecture. However one of the major challenges in service ...
Multi-Resolution Design for Large-Scale and High-Resolution Monitoring
Large-scale and high-resolution monitoring systems are ideal for many visual surveillance applications. However, existing approaches have insufficient resolution and low frame rate per second, or have high complexity and cost. We take inspiration from ...
Comments