Abstract
We introduce a model of uncertainty where documents are not uniquely identified in a reference network, and some links may be incorrect. It generalizes the probabilistic approach on databases to graphs, and defines subgraphs with a probability distribution. The answer to a relational query is a distribution of documents, and we study how to approximate the ranking of the most likely documents and quantify the quality of the approximation. The answer to a function query is a distribution of values and we consider the size of the interval of Minimum and Maximum values as a measure for the precision of the answer.
The work was supported by the German Academic Exchange Service.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Broder, A.Z., Glassman, S.C., Manasse, M.S., Zweig, G.: Syntactic clustering of the web. Computer Networks 29(8-13), 1157–1166 (1997)
Shivakumar, N., Garcia-Molina, H.: Finding near-replicas of documents on the web. In: Atzeni, P., Mendelzon, A.O., Mecca, G. (eds.) The World Wide Web and Databases. LNCS, vol. 1590, Springer, Heidelberg (1999)
Broder, A.Z.: Identifying and filtering near-duplicate documents. In: Giancarlo, R., Sankoff, D. (eds.) CPM 2000. LNCS, vol. 1848, pp. 1–10. Springer, Heidelberg (2000)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project (1998)
Andritsos, P., Fuxman, A., Miller, R.J.: Clean answers over dirty databases: A probabilistic approach. In: ICDE. Proceedings of the International Conference on Data Engineering (2006)
Fagin, R., Kumar, R., Mahdian, M., Sivakumar, D., Vee, E.: Comparing and aggregating rankings with ties. In: ACM Principles on Databases Systems, pp. 47–58. ACM Press, New York (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hess, C., de Rougemont, M. (2007). A Model of Uncertainty for Near-Duplicates in Document Reference Networks. In: Kovács, L., Fuhr, N., Meghini, C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2007. Lecture Notes in Computer Science, vol 4675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74851-9_40
Download citation
DOI: https://doi.org/10.1007/978-3-540-74851-9_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74850-2
Online ISBN: 978-3-540-74851-9
eBook Packages: Computer ScienceComputer Science (R0)