Privacy protected knowledge management in services with emphasis on quality data

Abstract

Improving productivity of practitioners through effective knowledge management and delivering high quality service in Application Management Services (AMS) domain, are key focus areas for all IT services organizations. One source of historical knowledge in AMS is the large amount of resolved problem ticket data which are often confidential, immensely valuable, but majority of it is of very bad quality. In this paper, we present a knowledge management tool that detects the quality of information present in problem tickets and enables effective knowledge search in tickets by prioritizing quality data in the search ranking. The tool facilitates leveraging of knowledge across different AMS accounts, while preserving data privacy, by masking client confidential information. It also extracts several relevant entities contained in the noisy unstructured text entered in the tickets and presents them to the users. We present several experimental evaluations and a pilot study conducted with an AMS account which show that our tool is effective and leads to substantial improvement in productivity of the practitioners. © 2011 ACM.