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A Framework for Decentralized Ranking in Web Information Retrieval
 

Summary: A Framework for Decentralized Ranking in Web
Information Retrieval
Karl Aberer and Jie Wu
School of Computer and Communication Sciences
Swiss Federal Institute of Technology (EPF), Lausanne
1015 Lausanne, Switzerland
{karl.aberer, jie.wu}@epfl.ch
Abstract. Search engines are among the most important applications
or services on the web. Most existing successful search engines use global
ranking algorithms to generate the ranking of documents crawled in
their databases. However, global ranking of documents has two potential
problems: high computation cost and potentially poor rankings. Both
of the problems are related to the centralized computation paradigm.
We propose to decentralize the task of ranking. This requires two
things: a decentralized architecture and a logical framework for ranking
computation. In the paper we introduce a ranking algebra providing
such a formal framework. Through partitioning and combining rankings,
we manage to compute document rankings of large-scale web data sets
in a localized fashion. We provide initial results, demonstrating that the
use of such an approach can ameliorate the above-mentioned problems.

  

Source: Aberer, Karl - Faculté Informatique et Communications, Ecole Polytechnique Fédérale de Lausanne

 

Collections: Computer Technologies and Information Sciences