A new approach for resolving conflicts in actionable behavioral rules

Peng Su, Dan Zhu, Dajun Zeng

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research.

Original languageEnglish (US)
Pages (from-to)530483
Number of pages1
JournalTheScientificWorldJournal [electronic resource]
Volume2014
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

prediction
ranking
Weights and Measures
experiment
Experiments
Research
method
conflict
parameter
test

ASJC Scopus subject areas

  • Medicine(all)

Cite this

A new approach for resolving conflicts in actionable behavioral rules. / Su, Peng; Zhu, Dan; Zeng, Dajun.

In: TheScientificWorldJournal [electronic resource], Vol. 2014, 2014, p. 530483.

Research output: Contribution to journalArticle

@article{8296f51517b2445883541dfb39dacb93,
title = "A new approach for resolving conflicts in actionable behavioral rules",
abstract = "Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research.",
author = "Peng Su and Dan Zhu and Dajun Zeng",
year = "2014",
doi = "10.1155/2014/530483",
language = "English (US)",
volume = "2014",
pages = "530483",
journal = "The Scientific World Journal",
issn = "1537-744X",
publisher = "Hindawi Publishing Corporation",

}

TY - JOUR

T1 - A new approach for resolving conflicts in actionable behavioral rules

AU - Su, Peng

AU - Zhu, Dan

AU - Zeng, Dajun

PY - 2014

Y1 - 2014

N2 - Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research.

AB - Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research.

UR - http://www.scopus.com/inward/record.url?scp=84929055230&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84929055230&partnerID=8YFLogxK

U2 - 10.1155/2014/530483

DO - 10.1155/2014/530483

M3 - Article

VL - 2014

SP - 530483

JO - The Scientific World Journal

JF - The Scientific World Journal

SN - 1537-744X

ER -