Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Expert deduction rules in data mining with association rules: a case study
Rauch J. Knowledge and Information Systems59 (1):167-195,2019.Type:Article
Date Reviewed: Aug 11 2020

The author uses logical calculus to create and prove deduction and expert deduction rules in this paper that deals with concepts and material about the analysis of domains and data mining.

The author starts by explaining foundational material in association rules and general unary hypotheses automaton (GUHA) association rules and their application to domain knowledge. He states his goals as introducing expert deduction rules and showing how their use can significantly reduce the number of output association rules for the given domain.

The paper is divided into six sections, starting with an introduction. The other sections cover GUHA association rules, domain knowledge and data mining, expert deduction rules and their applications, and an overview of related work.

The second section explains: “a GUHA association rule is an expression where [the variables] are Boolean attributes derived from columns of a data matrix.” It covers the development of a calculus of GUHA association rules, the use of Adult+ calculus, and the ASSOC procedure.

The third section introduces “domain knowledge and data mining with GUHA association rules.” It covers principles, items of domain knowledge and their atomic consequences, “agreed consequences and expert deduction rules,” and “logically correct deduction rules for dealing with domain knowledge.”

The fourth section covers “expert deduction rules for dealing with domain knowledge,” which includes preliminary considerations, principles and basic definitions, examples of results, and principles of application.

Section 5 includes application examples of expert deduction rules, expert deduction rules for experiments, “applying expert deduction rules to a priori results,” “applying expert deduction rules to GUHA association rules,” and a summary and open problems.

The last section (6), on “Related Work,” discusses how the material in this paper differs from other papers in the area and introduces expert deduction rules as both theoretically of interest and useful in a practical manner.

The material is well presented using proper logical tools, analysis, and methodology. It is well documented and has a thorough list of references. The author obviously knows the subject and does a good job in presenting it.

The paper is meant for readers who work in data mining and are familiar with logical calculus, deduction rules, and the methodology of these rules. It is advanced material and is not recommended for beginners.

Reviewer:  Michael Moorman Review #: CR147035 (2012-0297)
Bookmark and Share
  Reviewer Selected
Featured Reviewer
 
 
Data Mining (H.2.8 ... )
 
Would you recommend this review?
yes
no
Other reviews under "Data Mining": Date
Feature selection and effective classifiers
Deogun J. (ed), Choubey S., Raghavan V. (ed), Sever H. (ed) Journal of the American Society for Information Science 49(5): 423-434, 1998. Type: Article
May 1 1999
Rule induction with extension matrices
Wu X. (ed) Journal of the American Society for Information Science 49(5): 435-454, 1998. Type: Article
Jul 1 1998
Predictive data mining
Weiss S., Indurkhya N., Morgan Kaufmann Publishers Inc., San Francisco, CA, 1998. Type: Book (9781558604032)
Feb 1 1999
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy