EDM: A general framework for Data Mining based on Evidence Theory

Anand, Sarabjot Singh; Bell, David A.; Hughes, John G.

doi:10.1016/0169-023x(95)00038-t

Cited by 71 publications

(22 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The possibility of using such an operator has previously been mentioned by, for example, Yager 14 and is a generalization of the Proportional Belief Operator discussed by Anand et al 10 It may be thought of as a convex combination of the two mass allocations m 1 and m 2 . Proof.…”

Section: B the Weighted Sum Operatormentioning

confidence: 97%

“…It is described in detail in Guan and Bell,8,9 and previous work outlining how it may be used in data mining and for integration of distributed databases may be found in Anand et al, 10 McClean and Scotney, 11 and Scotney and McClean. 12 The framework provides a means of representing data in the form of a mass function which quantifies our degree of belief in various propositions.…”

Section: A Evidence Theorymentioning

confidence: 98%

See 1 more Smart Citation

Using evidence theory for the integration of distributed databases

McClean¹,

Scotney²

1997

Int. J. Intell. Syst.

View full text Add to dashboard Cite

Section: B the Weighted Sum Operatormentioning

confidence: 97%

Section: A Evidence Theorymentioning

confidence: 98%

Using evidence theory for the integration of distributed databases

McClean¹,

Scotney²

1997

Int. J. Intell. Syst.

View full text Add to dashboard Cite

“…Unlike neural networks, they are not black boxes; nevertheless they can become difficult to understand as well. Both neural networks [7] and tree induction [8] techniques have been employed for Data Mining, along with statistical techniques [6].…”

Section: Classification Of Data Mining Problemsmentioning

confidence: 99%

A framework for a World Wide Web-based Data Mining system

Wong

Nayar

Mikler

1998

Journal of Network and Computer Applications

View full text Add to dashboard Cite

“…The main purpose of evidence theory is to synthesize uncertain data from many sources. Evidence theory uses the formula of evidence synthesis to compose the credibility of different information sources so as to obtain decision-making results [40]. Skowron and Grzymala [41] proposed a method of evidence acquisition based on a decision table.…”

Section: Radial Basis Function (Rbf) Neural Network and Dempster-shafmentioning

confidence: 99%

Mobile e-Commerce Recommendation System Based on Multi-Source Information Fusion for Sustainable e-Business

Guo

Yin²,

Li³

et al. 2018

Sustainability

View full text Add to dashboard Cite

A lack of in-depth excavation of user and resources information has become the main bottleneck restricting the predictive analytics of recommendation systems in mobile commerce. This article provides a method which makes use of multi-source information to analyze consumers' requirements for e-commerce recommendation systems. Combined with the characteristics of mobile e-commerce, this method employs an improved radial basis function (RBF) network in order to determine the weights of recommendations, and an improved Dempster-Shafer theory to fuse the multi-source information. Power-spectrum estimation is then used to handle the fusion results and allow decision-making. The experimental results illustrate that the traditional method is inferior to the proposed approach in terms of recommendation accuracy, simplicity, coverage rate and recall rate. These achievements can further improve recommendation systems, and promote the sustainable development of e-business.

show abstract

EDM: A general framework for Data Mining based on Evidence Theory

Cited by 71 publications

References 9 publications

Using evidence theory for the integration of distributed databases

Using evidence theory for the integration of distributed databases

A framework for a World Wide Web-based Data Mining system

Mobile e-Commerce Recommendation System Based on Multi-Source Information Fusion for Sustainable e-Business

Contact Info

Product

Resources

About