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|Title: ||Relational link-based ranking|
|Authors: ||GEERTS, Floris|
|Issue Date: ||2004|
|Citation: ||Nascimento, M.A. & Kossmann, D. (Ed.) Proceedings of the 30th International Conference on Very Large Data Bases. p. 552-563.|
|Abstract: ||Link analysis methods show that the interconnections between web pages have lots of valuable information. The link analysis methods are, however, inherently oriented towards analyzing binary relations.
We consider the question of generalizing link analysis methods for analyzing relational databases. To this aim, we provide a generalized ranking framework and address its practical implications.
More specifically, we associate with each relational database and set of queries a unique weighted directed graph, which we call the database graph. We explore the properties of database graphs. In analogy to link analysis algorithms, which use the Web graph to rank web pages, we use the database graph to rank partial tuples. In this way we can, e.g., extend the PageRank link analysis algorithm to relational databases and give this extension a random querier interpretation.
Similarly, we extend the HITS link analysis algorithm to relational databases. We conclude with some preliminary experimental results.|
|Type: ||Proceedings Paper|
|Appears in Collections: ||Research publications|
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