@techreport{haveliwala2003analytical,
  abstract = {PageRank, the popular link-analysis algorithm for ranking web pages, assigns a query and user independent estimate of "importance" to web pages.  Query and user sensitive extensions of PageRank, which use a basis set of biased PageRank vectors, have been proposed in order to personalize the ranking function in a tractable way.  We analytically compare three recent approaches to personalizing PageRank and discuss the tradeoffs of each one.},
  address = {Stanford},
  author = {Haveliwala, Taher and Kamvar, Sepandar and Jeh, Glen},
  institution = {Stanford InfoLab},
  interhash = {6adad5ffe99f07fe8777fa7e95da4021},
  intrahash = {c0a97c488805a3b4349339439376ac44},
  month = jun,
  number = {2003-35},
  title = {An Analytical Comparison of Approaches to Personalizing PageRank},
  url = {http://ilpubs.stanford.edu:8090/596/},
  year = 2003
}

@article{jeh-simrank,
  author = {Jeh, G. and Widom, J.},
  interhash = {a6d4531690305dc44937118df813b4b5},
  intrahash = {ba5c057884730db377909072044ee03e},
  title = {{SimRank: A measure of structural-context similarity}},
  url = {http://scholar.google.de/scholar.bib?q=info:W8wKRBpAlMsJ:scholar.google.com/&output=citation&hl=de&ct=citation&cd=0},
  year = 2002
}