@inproceedings{719eac36a11742fe9c96285f0b1bed7f,
title = "Automatic Discovery of Service Name Replacements Using Ledger Data",
abstract = "Recent studies have illustrated historical financial data could be used to predict future revenues and profits. Prediction models would be accurate when long-run data that traces back for multiple years is available. However, changes in service structures often result in alteration of the nomenclatures of the services, making the streams of financial transactions associated with affected services discontinue. Manually inquiring the history of changes can be tedious and unsuccessful especially in large companies. In this paper, we propose a machine learning based algorithm for automatically discovering service name replacements. The proposed methodology draws heterogeneous features from financial data available in most ledger databases, and hence is generalizable. Our proposed methodology is shown to be effective on ground-truth synthesized data generated from real-world IBM service delivery ledger database.",
keywords = "Classification, Machine Learning, Service Name Replacement",
author = "Suppawong Tuarob and Tucker, \{Conrad S.\} and Ray Strong and Jeannette Blomberg and Anca Chandra and Pawan Chowdhary and Sechan Oh",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Conference on Services Computing, SCC 2015, co-located with the 2015 IEEE Congress on Services, SERVICES 2015 ; Conference date: 27-06-2015 Through 02-07-2015",
year = "2015",
month = aug,
day = "17",
doi = "10.1109/SCC.2015.90",
language = "English",
series = "Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "624--631",
editor = "Maglio, \{Paul P.\} and Incheon Paik and Wu Chou",
booktitle = "Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015",
}