@inproceedings{047fa6d20cf9411ebda8e7b88a73ab01,
title = "Contextual Analysis of Transactional Data",
abstract = "Data analysis is often attempted by business stakeholder on transactional databases, that are maintained within the overall enterprise system, in order to understand patterns of user behavior, transaction types, and their impact on the utility and value of interest to the enterprise. Statistical and machine learning techniques are often used to make predictions and decisions. In order to guide the business stakeholder ask the right questions and guide the query processor in fetching the most accurate answers to the questions we introduce formal approaches in which the five dimensional context information What?, Why?, Where?, When?, Who? are captured. When the transactions are contextually qualified both querying and analysis of data on their responses will lead to efficient and accurate discovery of interesting patterns for decision making.",
keywords = "Contextual analysis, Data analysis, Formalization, Information system, Transactional data",
author = "Vangalur Alagar and Kaiyu Wan",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 ; Conference date: 20-07-2019 Through 22-07-2019",
year = "2020",
doi = "10.1007/978-3-030-32591-6_115",
language = "English",
isbn = "9783030325909",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "1054--1062",
editor = "Yong Liu and Lipo Wang and Liang Zhao and Zhengtao Yu",
booktitle = "Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery - Volume 2",
}