Skip to main content

Cognitive Computing to Optimize IT Services.

Ali, A.R., 2018. Cognitive Computing to Optimize IT Services. In: 2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 16-18 July 2018, Berkeley, CA, USA, 54 - 60.

Full text available as:

[img]
Preview
PDF
Cognitive Computing to Optimize IT Services.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

699kB

DOI: 10.1109/ICCI-CC.2018.8482078

Abstract

In this paper, the challenges of maintaining a healthy IT operational environment have been addressed by proactively analyzing IT Service Desk tickets, customer satisfaction surveys and social media data. A Cognitive solution goes beyond the traditional structured data analysis solutions by deep analyses of both structured and unstructured text. The salient features of the proposed platform include language identification, translation, hierarchical extraction of the most frequently occurring topics, entities and their relationships, text summarization, sentiments and knowledge extraction from the unstructured text using Natural Language Processing techniques. Moreover, the insights from unstructured text combined with structured data allows the development of various classification, segmentation and time-series forecasting use-cases on incident, problem and change datasets. The text and predictive insights together with raw data are used for visualization and exploration of actionable insights on a rich and interactive dashboard. However, it is hard not only to find these insights using traditional Analytics solutions but it might also take very long time to discover them, especially while dealing with massive amount of unstructured data. By taking actions on these insights, organizations can benefit from significant reduction of ticket volume, reduced operational costs and increased customer satisfaction. In various experiments, on average, up to 18-25 % of yearly ticket volume has been reduced using the proposed approach.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Knowledge Extraction ; Optimizing IT Services ; Cognitive Computing ; Topic Clustering ; Semantic Text Analytics ; Service Desk
Group:Faculty of Science & Technology
ID Code:34261
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:08 Jul 2020 09:45
Last Modified:08 Jul 2020 09:45

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -