NDLI: A statistical machine learning approach for ticket mining in IT service delivery

Content Provider	IEEE Xplore Digital Library
Author	Ea-Ee Jan Jian Ni Niyu Ge Ayachitula, N. Xiaolan Zhang
Copyright Year	2013
Description	Author affiliation: IBM T.J. Watson Res. Center, Hawthorne, NY, USA (Ea-Ee Jan; Jian Ni; Niyu Ge; Ayachitula, N.; Xiaolan Zhang)
Abstract	Ticketing is a fundamental management process of IT service delivery. Customers typically express their requests in the form of tickets related to problems or configuration changes of existing systems. Tickets contain a wealth of information which, when connected with other sources of information such as asset and configuration information, monitoring information, can yield new insights that would otherwise be impossible to gain from one isolated source. Linking these various sources of information requires a common key shared by these data sources. The key is the server names. Unfortunately, due to historical as well as practical reasons, the server names are not always present in the tickets as a standalone field. Rather, they are embedded in unstructured text fields such as abstract and descriptions. Thus, automatically identifying server names in tickets is a crucial step in linking various information sources. In this paper, we present a statistical machine learning method called Conditional Random Field (CRF) that can automatically identify server names in tickets with high accuracy and robustness. We then illustrate how such linkages can be leveraged to create new business insights.
Starting Page	541
Ending Page	546
File Size	320138
Page Count	6
File Format	PDF
ISBN	9781467352291
e-ISBN	9783901882500
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-27
Publisher Place	Belgium
Access Restriction	Subscribed
Rights Holder	IFIP
Subject Keyword	Servers Dictionaries Data models Training data Business Training Robustness Machine Learning Service management Data model Analytics Statistical Models
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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