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Choose the Damping, Choose the Ranking?

  • Conference paper
Algorithms and Models for the Web-Graph (WAW 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5427))

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Abstract

To what extent can changes in PageRank’s damping factor affect node ranking? We prove that, at least on some graphs, the top k nodes assume all possible k! orderings as the damping factor varies, even if it varies within an arbitrarily small interval (e.g. [0.84999, 0.85001]). Thus, the rank of a node for a given (finite set of discrete) damping factor(s) provides very little information about the rank of that node as the damping factor varies over a continuous interval.

We bypass this problem introducing lineage analysis and proving that there is a simple condition, with a “natural” interpretation independent of PageRank, that allows one to verify “in one shot” if a node outperforms another simultaneously for all damping factors and all damping variables (informally, time variant damping factors). The novel notions of strong rank and weak rank of a node provide a measure of the fuzziness of the rank of that node, of the objective orderability of a graph’s nodes, and of the quality of results returned by different ranking algorithms based on the random surfer model.

We deploy our analytical tools on a 41M node snapshot of the .it Web domain and on a 0.7M node snapshot of the CiteSeer citation graph. Among other findings, we show that rank is indeed relatively stable in both graphs; that “classic” PageRank (d = 0.85) marginally outperforms Weighted In-degree (d→0), mainly due to its ability to ferret out “niche” items; and that, for both the Web and CiteSeer, the ideal damping factor appears to be 0.8 − 0.9 to obtain those items of high importance to at least one (model of randomly surfing) user, but only 0.5 − 0.6 to obtain those items important to every (model of randomly surfing) user.

This work was supported in part by MIUR under PRIN Mainstream and by EU under Integr. Proj. AEOLUS (IP-FP6-015964).

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Bressan, M., Peserico, E. (2009). Choose the Damping, Choose the Ranking?. In: Avrachenkov, K., Donato, D., Litvak, N. (eds) Algorithms and Models for the Web-Graph. WAW 2009. Lecture Notes in Computer Science, vol 5427. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95995-3_7

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  • DOI: https://doi.org/10.1007/978-3-540-95995-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-95994-6

  • Online ISBN: 978-3-540-95995-3

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