Publication Type

Conference Paper

Publication Date

11-2017

Abstract

Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these graphs and are used for estimatingvalue veracity and initializing existing data fusion methods. Empiricalstudies on two large real-world datasets demonstrate the effectiveness ofour approach.

Keywords

Data integration, Data fusion, Multi-valued data items, Inter-source agreements

Discipline

Databases and Information Systems | Data Storage Systems

Publication

36th International Conference on Conceptual Modeling, Valencia, Spain, 2017 November 6-9

Identifier

10.1007/978-3-319-69904-2_13

Publisher

Academy of Management

City or Country

Valencia, Spain

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1007/978-3-319-69904-2_13

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