Classification of objective interestingness measures

Lan Phuong Phan; Nghia Quoc Phan; Vinh Cong Phan; Hung Huu Huynh; Hiep Xuan Huynh; Fabrice Guillet

doi:10.60692/1dtrx-r3q60

ScienceGate Book Chapters

JOURNAL ARTICLE

Classification of objective interestingness measures

Lan Phuong Phan Nghia Quoc Phan Vinh Cong Phan Hung Huu Huynh Hiep Xuan Huynh Fabrice Guillet

Year: 2016 Journal: Greater South Information System

DOI: 10.60692/1dtrx-r3q60

Get Full-Text PDF Get Analytical Report

Abstract

The creation of the interestingness measures for evaluating the quality of the association rule - based knowledge plays an important role in the post-processing of the Knowledge Discovery from Databases. More and more interestingness measures are proposed by two approaches (subjective assessment and

Keywords:

Quality (philosophy) Measure (data warehouse) Knowledge extraction Association (psychology) Quality assessment

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.22

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

AI-based Problem Solving and Planning

Physical Sciences → Computer Science → Artificial Intelligence

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Classification of objective interestingness measures

Abstract

Metrics

Topics

Related Documents

Classification of objective interestingness measures

Classification of objective interestingness measures

Context-Aware Recommendation with Objective Interestingness Measures

A Unified View of Objective Interestingness Measures

On Mining Summaries by Objective Measures of Interestingness