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Author
Cherifi Walid (Military University of Technology in Warsaw, Poland), Szafrański Bolesław (Military University of Technology in Warsaw, Poland), Bliźniuk Grzegorz (Military University of Technology in Warsaw, Poland)
Title
Nowa metoda rozwiązywania konfliktów danych w procesie integracji informacji bazująca na dowodach
Towards evidence-based data conflict resolution in data integration process
Source
Roczniki Kolegium Analiz Ekonomicznych / Szkoła Główna Handlowa, 2015, nr 38, s. 44-55, bibliogr. 17 poz.
Keyword
Internet, Rozwiązywanie konfliktów, Przetwarzanie informacji, Teoria Demstera-Shafera
Internet, Solving conflicts, Information processing, Dempster-Shafer theory
Note
streszcz., summ
Abstract
W dzisiejszych czasach, wraz ze wzrostem użycia danych w Internecie oraz publicznych rejestrach, dane tworzone są w coraz większej ilości zarówno przez maszyny, jak i przez ludzi. Z powodu tej eksplozji danych pozyskiwanie dokładnych informacji z wielu rozproszonych źródeł jest skomplikowane. Fuzja danych, zwana również rozwiązywaniem konfliktów (ang. conflict resolution), jest istotnym etapem w procesie integracji danych. Jej celem jest rozwiązywanie konfliktów pomiędzy sprzecznymi informacjami dotyczącymi tego samego rzeczywistego obiektu. W tym artykule przedstawiamy nową metodologię rozwiązywania tego problem, która wykorzystuje siłę teorii Dempstera-Shafera. (abstrakt oryginalny)

The public sector in Poland and other countries is made up of many different organizations, ranging from large government departments to universities, health care facilities and libraries. Moreover, it generally comprises of different segments, i.e. defence, finance, education, health, environment etc. They each face different challenges, but the common theme for these diverse segments is the need for efficiency, visibility, and transparency. This decentralized structure of public administration suggests that in certain cases public agencies at different administration levels and different functional areas produce, gather, and disseminate similar data i.e. data about the same real-world objects. This situation results in a number of challenges regarding the quality of data, as it is possible that the disseminated data is incomplete, controversial and/or obsolete.Therefore, finding ways to integrate and bring diverse data sets together has the potential to increase the government's transparency, improve the functioning of public administration, contribute to economic growth and provide social value to citizens.However, to reach this goal, a difficult technical problem has to be solved first: the integration of typically distributed, inherently heterogeneous, and possibly inconsistent data sources.(original abstract)
Accessibility
The Library of Warsaw School of Economics
The Main Library of Poznań University of Economics and Business
Bibliography
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  1. Bleiholder, J., Naumann, F., Data fusion, "ACM Computing Surveys" 2008, vol. 41, no. 1, pp. 1-41.
  2. Blanco L., Crescenzi V., Merialdo P., Papotti P., Probabilistic models to reconcile complex data from inaccurate data sources, Conference on Advanced Information Systems Engineering 2010, pp. 83-97.
  3. Dempster A. P., Upper and Lower probabilities induced by a multivalued mapping, "Annals of Mathematical Statistics" 1967, vol. 38, pp. 325-339.
  4. Dong X. L., Berti-Equille L., Srivastava D., Integrating conflicting data: The role of source dependence, Proceedings of the VLDB 2009, vol. 2, no. 1, pp. 550-561.
  5. Dong X. L., Berti-Equille L., Srivastava D., Truth discovery and copying detection in a dynamic world, Proceedings of the VLDB 2009, vol. 2, no. 1, p. 573.
  6. Dong X. L., Saha B., Srivastava D., Less is more: Selecting sources wisely for integration, Proceedings of the VLDB 2013 vol. 6, no. 2.
  7. Elouedi Z., Mellouli K., Smets P., Assessing sensor reliability for multisensor data fusion within the transferable belief model, "IEEE Transactions on Systems, Man, and Cybernetics" 2004,vol. 34, no. 1, pp. 782-787.
  8. Fatehali M., Building the business case for Master Data Management in the Public Sector, "Oracle White Paper" 2011.
  9. Kalampokis E., Tambouris E., Tarabanis K., Open government data: A stage model, "Electronic Government" 2011, Lecture Notes in Computer Science 6846, pp. 235-246.
  10. Li Q., Li Y., Gao J., Zhao B., Fan W., Han J., Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation, Proceedings of the 2014 SIGMOD Conference.
  11. Li X., Dong X. L., Lyons K. B., Meng W., Srivastava D., Truth finding on the deep web: Is the problem solved?, Proceedings of the VLDB 2013, vol. 6, no. 2.
  12. Shafer G., A mathematical theory of evidence, Princeton University Press 1976.
  13. Sentz K., Ferson S., Combination of evidence in Dempster-Shafer theory, SANDIA Technical Report 2002, SAND2002-0835.
  14. Smets P., Decision making in the TBM: the necessity of the pignistic transformation, "International Journal of Approximate Reasoning" 2005, vol. 38, pp. 133-147.
  15. Yin X., Han J., Yu P. S., Truth discovery with multiple conflicting information providers on the web, Knowledge and Data Engineering, IEEE Transactions on 20.6 (2008), pp. 796-808.
  16. Yin X., Tan W., Semi-supervised truth discovery, Proceedings from the WWW Conference 2011, pp. 217-226.
  17. Ziemba E., Obłąk I., The survey of information systems in public administration in Poland, "Interdisciplinary Journal of Information, Knowledge and Management" 2011, vol. 9, pp. 31-56.
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ISSN
1232-4671
Language
eng
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