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A Data-Driven Knowledge Acquisition System- An End-to-End Knowledge Engineering Process for Generating Production Rules.pdf (2.88 MB)

A data-driven knowledge acquisition system: an end-to-end knowledge engineering process for generating production rules

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journal contribution
posted on 2023-05-19, 17:05 authored by Ali, M, Ali, R, Khan, WA, Han, SC, Bang, J, Hur, T, Kim, D, Lee, S, Byeong KangByeong Kang
Data-driven knowledge acquisition is one of the key research fields in data mining. Dealing with large amounts of data has received a lot of attention in the field recently, and a number of methodologies have been proposed to extract insights from data in an automated or semi-automated manner. However, these methodologies generally target a specific aspect of the data mining process, such as data acquisition, data preprocessing, or data classification. However, a comprehensive knowledge acquisition method is crucial to support the end-to-end knowledge engineering process. In this paper, we introduce a knowledge acquisition system that covers all major phases of the cross-industry standard process for data mining. Acknowledging the importance of an end-to-end knowledge engineering process, we designed and developed an easy-to-use data-driven knowledge acquisition tool (DDKAT). The major features of the DDKAT are: (1) a novel unified features scoring approach for data selection; (2) a user-friendly data processing interface to improve the quality of the raw data; (3) an appropriate decision tree algorithm selection approach to build a classification model; and (4) the generation of production rules from various decision tree classification models in an automated manner. Furthermore, two diabetes studies were performed to assess the value of the DDKAT in terms of user experience. A total of 19 experts were involved in the first study and 102 students in the artificial intelligence domain were involved in the second study. The results showed that the overall user experience of the DDKAT was positive in terms of its attractiveness, as well as its pragmatic and hedonic quality factors.

Funding

Ministry of Trade, Industry and Energy

History

Publication title

IEEE Access

Volume

6

Pagination

15587-15607

ISSN

2169-3536

Department/School

School of Information and Communication Technology

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

United States

Rights statement

Copyright 2018 IEEE

Repository Status

  • Open

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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