Propagation of Uncertainty by the Possibility Theory in Choquet Integral-Based Decision Making: Application to an E-Commerce Website Choice Support

Denguir-Rekik, A.; Mauris, Gilles; Montmain, Jacky

doi:10.1109/tim.2006.873803

Cited by 22 publications

(15 citation statements)

References 15 publications

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“…Resulting from this ability to handle uncertain and incomplete information, the possibility theory has been used successfully in a wide range of engineering and scientific fields, including decision making [14], instance-based learning [25], and database query systems [29].…”

Section: Possibility Theorymentioning

confidence: 99%

Knowledge discovery of customer purchasing intentions by plausible-frequent itemsets from uncertain data

Weng

Huang

2015

Appl Intell

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Many previous studies have focused on the extraction of association rules from transaction data. Unfortunately, customer purchasing intentions tend to be uncertain during the decision making process. That is, they cannot be obtained from business transaction data. Therefore, the research problem is how to discover frequent itemsets from uncertain data. This study first proposes a new model to represent consumer uncertainty during the decision making process. This representation scheme is based on possibility distributions. The possibility theory provides an excellent framework for handling uncertain data. In addition, an algorithm is developed to mine plausible-frequent itemsets from uncertain data, which are represented by possibility distributions, and then discover plausible association rules based on these plausible-frequent itemsets. Experimental results show that the proposed model can discover interesting plausible-frequent patterns from survey data which represent customer purchasing decisions.

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Section: Possibility Theorymentioning

confidence: 99%

Knowledge discovery of customer purchasing intentions by plausible-frequent itemsets from uncertain data

Weng

Huang

2015

Appl Intell

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“…The Choquet integral approach of propagating a special uncertainty of possibility theory is analyzed in [26] to have a formidable application in solving the problem of choice encountered in an electronic commerce website during purchasing activity.…”

Section: Review Of Existing Literature On Possibility Theory and Its mentioning

confidence: 99%

Analysis of Possibility Theory for Reasoning under Uncertainty

Alola¹,

Tunay²,

Alola³

2013

IJSP

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The purpose of this thesis is to analyze the possibility theory for reasoning under uncertainty. The relationship and difference between probability and possibility theories are presented. The areas of application of possibility theory are studied. The advantages of possibility theory over the probability theory in modeling uncertainty are described. The quantitative and qualitative possibilities are considered. The possibility measure, the possibility distribution and the imprecise probability are discussed.

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“…Attributing an overall score to an EC in the FBDS framework is then meaningful because the aggregation step models the evaluation strategy of the marketing staff. For the sake of simplicity, only WAM aggregations are considered in this paper (more sophisticated operators have been studied in Denguir et al (2006a). The WAM aggregation models the marketing team evaluation strategy relatively to the set of criteria.…”

Section: From a Recommendation System To A Diagnosis Support Systemmentioning

confidence: 99%

A possibilistic-valued multi-criteria decision-making support for marketing activities in e-commerce: Feedback Based Diagnosis System

Denguir-Rekik

Montmain

Mauris

2009

European Journal of Operational Research

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In this paper we propose a multi-criteria decision making support system, called a ''Feedback Based Diagnosis System" (FBDS), to aid the marketing team of an e-commerce (EC) organisation in its activities. The FBDS database is composed of customers' satisfaction measures. These measures are related to the different services an EC offers to its customers. Thus, they constitute a multi-criteria (MC) evaluation of EC performances. In the general framework of recommender systems, these available MC evaluations are considered as useful information for other customers to help them to objectively, rationally and exhaustively assess and compare the numerous ECs among the ones likely to meet their needs. Our FBDS is not concerned with improving or automating such a recommendation process for customers. Indeed, it is merely EC management team oriented. In fact, the MC feedback database is used to diagnose the EC health and improve its strategy. In the proposed FBDS, a possibilistic framework is combined with the multi criteria representation to capture the variability and the divergence of customers' evaluations w.r.t. each criterion. Then, an aggregation based on a weighted arithmetic mean (WAM) is proposed to obtain a synthetic appraisal of ECs. The WAM aggregation models the strategy agreed on by the EC management team. Computing the synthesis score of an EC consists in propagating the uncertainty related to its partial scores through the WAM. The possibilistic representation guarantees that no information is lost in the collective evaluation process by the consumers' community. However, diagnosis indicators are finally proposed to the marketing team to make the interpretation of some possibilistic results more comprehensive when necessary.

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Propagation of Uncertainty by the Possibility Theory in Choquet Integral-Based Decision Making: Application to an E-Commerce Website Choice Support

Cited by 22 publications

References 15 publications

Knowledge discovery of customer purchasing intentions by plausible-frequent itemsets from uncertain data

Knowledge discovery of customer purchasing intentions by plausible-frequent itemsets from uncertain data

Analysis of Possibility Theory for Reasoning under Uncertainty

A possibilistic-valued multi-criteria decision-making support for marketing activities in e-commerce: Feedback Based Diagnosis System

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