Maximal fusion of facts on the web with credibility guarantee

Nguyên, Thành Tâm; Phan, Truong Khoa; Nguyen, Quoc Viet Hung; Aberer, Karl; Stantić, Bela

doi:10.1016/j.inffus.2018.07.009

Cited by 19 publications

(12 citation statements)

References 42 publications

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“…To model the different factors or the reliability of different sources, credibility analysis is a possible way . To reflect the credibility relations among the collected probability distribution, different types of credibility functions have been presented …”

Section: Proposed Methodsmentioning

confidence: 99%

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Aggregation of uncertainty data based on ordered weighting aggregation and generalized information quality

Xiao

2019

Int J Intell Syst

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It is necessary to take the information quality into consideration in information fusion. However, existing information quality has a limitation due to the ignorance of the credibility of information source. In this paper, the generalized information quality (GIQ) been proposed considering the association among the collected sensor reports, first. Then, the ordered weighting aggregation (OWA) operator of probability distribution based on the GIQ is presented. Numerical example and real application in fault diagnosis are used to illustrate the efficiency of the proposed method. The proposed GIQ and OWA algorithm has the advantage in fault tolerance and reduce the impact of conflict data in data fusion process, due to the consideration of the credibility of each sensor report. The proposed method has the promising aspects in uncertainty data aggregation.

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Section: Proposed Methodsmentioning

confidence: 99%

“…49 To reflect the credibility relations among the collected probability distribution, different types of credibility functions have been presented. 30,50 It is reasonable to calculate the degree of credibility with the use of the similarity of the probability distribution, determined by the degree of support.…”

Section: Calculate Credibilitymentioning

confidence: 99%

Aggregation of uncertainty data based on ordered weighting aggregation and generalized information quality

Xiao

2019

Int J Intell Syst

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“…Network-level constraints were originally considered in [69,12], in which the establishment of semantic interoperability in large-scale P2P networks was studied. As discussed earlier, these ideas have been adopted for integrity constraints in the reconciliation process of database schemas in [11,13,70]. Yet, these approaches put forward a simplistic view on data models and, thus, integrity constraints.…”

Section: Related Workmentioning

confidence: 99%

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Hùng

Weidlich

Tâm

et al. 2019

Information Systems

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Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and electronic commerce to social networking. Many of these applications involve models of diverse data sources. Effective utilisation and evolution of data models, therefore, calls for matching techniques that generate correspondences between their elements. Various such matching tools have been developed in the past. Yet, their results are often incomplete or erroneous, and thus need to be reconciled, i.e., validated by an expert. This paper analyses the reconciliation process in the presence of large collections of data models, where the network induced by generated correspondences shall meet consistency expectations in terms of integrity constraints. We specifically focus on how to handle data models that show some internal structure and potentially differ in terms of their assumed level of abstraction. We argue that such a setting calls for a probabilistic model of integrity constraints, for which satisfaction is preferred, but not required. In this work, we present a model for probabilistic constraints that enables reasoning on the correctness of individual correspondences within a network of data models, in order to guide an expert in the validation process. To support pay-as-you-go reconciliation, we also show how to construct a set of high-quality correspondences, even if an expert validates only a subset of all generated correspondences. We demonstrate the efficiency of our techniques for real-world datasets comprising database schemas and ontologies from various application domains.

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“…Information quality is firstly proposed by Yager and Petry based on Gini entropy to measure the uncertainty for a probability distribution [32], [33]. It has been widely used in pattern classification [34], [35], decision making [36], [37] and so on [38]- [43], [43], [44]. Li et al propose a generalized expression for information quality in basic probability assignment in Dempster-Shafer evidence theory [45], which makes information quality have greater scope of application.…”

Section: Introductionmentioning

confidence: 99%

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

Li¹,

Cai²

2020

Preprint

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<div>Information quality is widely used in many applications. However, how to measure information quality in basic probability assignment accurately is still an open issue. Generalized expression for information quality is an effective method to measure information quality in basic probability assignment. Nevertheless, the counter-intuitive results may be obtained when statements are of intersection. To address this issue, a new expression for information quality of basic probability assignment is proposed in this paper considering the frame of discernment and the influence of intersection among statements which can cause changes of uncertainty. Numerical examples are illustrated to demonstrate the effectiveness of the proposed method. In addition, an application in fault diagnosis is used to show the effectiveness of the proposed method. </div>

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Maximal fusion of facts on the web with credibility guarantee

Cited by 19 publications

References 42 publications

Aggregation of uncertainty data based on ordered weighting aggregation and generalized information quality

Aggregation of uncertainty data based on ordered weighting aggregation and generalized information quality

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

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