Ranking information in networks

Authors:
Tina Eliassi-Rad;Keith Henderson
Affiliations:
Rutgers University;Lawrence Livermore National Laboratory
Venue:
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Year:
2011

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Abstract

Given a network, we are interested in ranking sets of nodes that score highest on user-specified criteria. For instance in graphs from bibliographic data (e.g. PubMed), we would like to discover sets of authors with expertise in a wide range of disciplines. We present this ranking task as a Top-K problem; utilize fixed-memory heuristic search; and present performance of both the serial and distributed search algorithms on synthetic and real-world data sets.