TupleRank: Ranking Relational Databases using Random Walks on Extended K-partite GraphsReport as inadecuate




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Random Walk, Database Systems, database ranking, bipartite graph



Date created: 2009

DOI: doi:10.7939-R3WS8HP9D

License information: Creative Commons Attribution 3.0 Unported

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Author: Chen, Jiyang Zaiane, Osmar R. Goebel, Randy Yu, Philip S.

Source: https://era.library.ualberta.ca/


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TupleRank: Ranking Relational Databases using Random Walks on Extended K-partite Graphs Jiyang Chen 1 , Osmar R.
Zaı̈ane 1 , Randy Goebel 1 , Philip S.
Yu 1 Department of Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8 1 2 2 {jiyang, zaiane, goebel}@cs.ualberta.ca Department of Computer Science, University of Illinois at Chicago 851 S.
Morgan St., Rm 1138 SEO, Chicago, IL 60607 2 psyu@cs.uic.edu No Institute Given Abstract.
The significant increase in open access digital information has created incredible opportunities for modern database research, especially in exploiting significant computational resources to determine complex relationships within those data.
In this paper, we consider the problem of analyzing relational databases and explaining relationships between entities in order to rank tuples based on a notion of relevance. For this purpose, we propose a solution of a class of link analysis algorithms known as the random walk, which can be deployed to discover interesting relationships amongst partial tuples of relational databases that would otherwise be hard to expose.
We focus on a shortcoming of the absence of a special kind of relationship, which we call “returning relationship”.
We demonstrate our ideas on the DBLP database, where we exploit structural variations on relationships between authors, conferences, topics, and co-authorships.
We show how a distinction between normal relations and returning relations on objects within that database provides the basis for structuring a random walk algorithm to determine interesting relevance measures.
We also show how structural changes in the organization of the random walk can produce novel results that are not attainable with previous database ranking methods. 1 Introduction Ranking, i.e., a process of positioning entities on an ordinal scale in relation to others, is an important task that has a significant role in many applications. In large databases, users wo...





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