Paper Info
Title
Relational link-based ranking
Abstract
Link analysis methods show that the intercon- nections between web pages have lots of valu- able information. The link analysis methods are, however, inherently oriented towards an- alyzing binary relations. We consider the question of generalizing link analysis methods for analyzing relational databases. To this aim, we provide a general- ized ranking framework and address its prac- tical implications. More speciflcally, we associate with each rela- tional 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., ex- tend the PageRank link analysis algorithm to relational databases and give this extension a random querier interpretation. Similarly, we extend the HITS link analysis al- gorithm to relational databases. We conclude with some preliminary experimental results.
Year
DOI
Venue
2004
10.1016/B978-012088469-8.50050-4
VLDB
Keywords
Field
DocType
web graph,web page,generalizing link analysis method,analysis algorithm,link analysis method,relational databases,relational database,pagerank link analysis algorithm,hits link analysis algorithm,database graph,relational link-based ranking,binary relation,directed graph,link analysis,web pages
Data mining,Conjunctive query,Relational calculus,Graph database,Relational database,Database model,Computer science,Theoretical computer science,Database design,Wait-for graph,Relational model,Database
Conference
ISBN
Citations 
PageRank 
0-12-088469-0
39
3.15
References 
Authors
17
3
Name
Order
Citations
PageRank
Floris Geerts11570104.70
Heikki Mannila265951495.69
Evimaria Terzi3158083.54