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.
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References
Frederickson, G.N., Johnson, D.B.: Generalized selection and ranking. In: Proc. of the 12th STOC, pp. 420–428 (1980)
Fredman, M.L.: How good is the information theory bound in sorting? Theoretic. Comput. Sci. 1, 355–361 (1976)
Hart, P.E., Nilsson, N.J., Raphael, B.: Correction to a formal basis for the heuristic determination of minimum cost paths. SIGART Bull. 37, 28–29 (1972)
Russell, S.: Efficient memory-bounded search methods. In: ECAI, pp. 1–5 (1992)
Russell, S.J.: Efficient memory-bounded search methods. In: Proc of the 10th ECAI, pp. 1–5 (1992)
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© 2011 Springer-Verlag Berlin Heidelberg
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Eliassi-Rad, T., Henderson, K. (2011). Ranking Information in Networks. In: Salerno, J., Yang, S.J., Nau, D., Chai, SK. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2011. Lecture Notes in Computer Science, vol 6589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19656-0_38
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DOI: https://doi.org/10.1007/978-3-642-19656-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19655-3
Online ISBN: 978-3-642-19656-0
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