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Truth discovery with multiple conflicting information providers on the web

Published: 12 August 2007 Publication History

Abstract

The world-wide web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the web. Moreover, different web sites often provide conflicting information on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity, i.e., conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various web sites. We design a general framework for the Veracity problem, and invent an algorithm called TruthFinder, which utilizes the relationships between web sites and their information, i.e., a web site is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy web sites. Our experiments show that TruthFinder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.

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References

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A. Borodin, G. Roberts, J. Rosenthal, P. Tsaparas. Link analysis ranking: Algorithms, theory, and experiments. ACM Transactions on Internet Technology, 5(1):231--297, 2005.
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J. M. Kleinberg. Authoritative sources in a hyperlinked environment. In SODA, 1998.
[3]
Logistical Equation from Wolfram MathWorld. http://mathworld.wolfram.com/LogisticEquation.html
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L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank citation ranking: bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
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Princeton Survey Research Associates International. Leap of faith: using the Internet despite the dangers. Results of a National Survey of Internet Users for Consumer Reports WebWatch, Oct 2005.
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Sigmoid Function from Wolfram MathWorld. http://mathworld.wolfram.com/SigmoidFunction.html

Cited By

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  • (2025)Hyper-parameter Recommendation for Truth DiscoveryDatabase Systems for Advanced Applications10.1007/978-981-97-5555-4_18(277-292)Online publication date: 12-Jan-2025
  • (2024)High Precision ≠ High Cost: Temporal Data Fusion for Multiple Low-Precision SensorsProceedings of the ACM on Management of Data10.1145/36549462:3(1-27)Online publication date: 30-May-2024
  • (2024)Trustworthiness Evaluation of Internet of Vehicles Nodes Based on Real-Time Perception and Long-Term Reputation2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS61622.2024.10606703(1081-1086)Online publication date: 17-May-2024
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    cover image ACM Conferences
    KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
    August 2007
    1080 pages
    ISBN:9781595936097
    DOI:10.1145/1281192
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 12 August 2007

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    Author Tags

    1. data quality
    2. link analysis
    3. web mining

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    KDD '07 Paper Acceptance Rate 111 of 573 submissions, 19%;
    Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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    Cited By

    View all
    • (2025)Hyper-parameter Recommendation for Truth DiscoveryDatabase Systems for Advanced Applications10.1007/978-981-97-5555-4_18(277-292)Online publication date: 12-Jan-2025
    • (2024)High Precision ≠ High Cost: Temporal Data Fusion for Multiple Low-Precision SensorsProceedings of the ACM on Management of Data10.1145/36549462:3(1-27)Online publication date: 30-May-2024
    • (2024)Trustworthiness Evaluation of Internet of Vehicles Nodes Based on Real-Time Perception and Long-Term Reputation2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)10.1109/DDCLS61622.2024.10606703(1081-1086)Online publication date: 17-May-2024
    • (2024)Representing the Uncertainty of a 3D Geological Model via Global Optimum Truth Discovery TechnologyNatural Resources Research10.1007/s11053-024-10404-734:1(171-192)Online publication date: 23-Sep-2024
    • (2024)Truth Discovery Against Disguised Attack Mechanism in CrowdsourcingWeb and Big Data10.1007/978-981-97-2387-4_5(64-79)Online publication date: 28-Apr-2024
    • (2024)Truth Discovery of Source Dependency Perception in Dynamic ScenariosWeb and Big Data10.1007/978-981-97-2387-4_4(48-63)Online publication date: 28-Apr-2024
    • (2023)Examining Knowledge Extraction Processes from Heterogeneous Data SourcesBrilliant Engineering10.36937/ben.2023.47984:1(1-8)Online publication date: 8-Feb-2023
    • (2023)A Crowdsourced Learning Framework to Optimize Cross-Event QoS in AI-powered Social Sensing2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SECON58729.2023.10287448(429-437)Online publication date: 11-Sep-2023
    • (2023)Finding the Truth From Uncertain Time Series by DifferencingIEEE Open Journal of the Computer Society10.1109/OJCS.2023.33261504(303-313)Online publication date: 2023
    • (2023)A truth value discovery algorithm for conflict sensor data in sensor network2023 35th Chinese Control and Decision Conference (CCDC)10.1109/CCDC58219.2023.10327002(4435-4440)Online publication date: 20-May-2023
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