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RoundTripRank: Graph-based proximity with importance and specificity?

Graph-based proximity has many applications with different ranking needs. However, most previous works only stress the sense of importance by finding "popular" results for a query. Often times important results are overly general without being well-tailored to the query, lacking a sense of...

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Main Authors: Yuan Fang, Chang, K. C-C, Lauw, H. W.
Format: Conference Proceeding
Language:English
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Chang, K. C-C
Lauw, H. W.
description Graph-based proximity has many applications with different ranking needs. However, most previous works only stress the sense of importance by finding "popular" results for a query. Often times important results are overly general without being well-tailored to the query, lacking a sense of specificity - which only emerges recently. Even then, the two senses are treated independently, and only combined empirically. In this paper, we generalize the well-studied importance-based random walk into a round trip and develop RoundTripRank, seamlessly integrating specificity and importance in one coherent process. We also recognize the need for a flexible trade-off between the two senses, and further develop RoundTripRank+ based on a scheme of hybrid random surfers. For efficient computation, we start with a basic model that decomposes RoundTripRank into smaller units. For each unit, we apply a novel two-stage bounds updating framework, enabling an online top-K algorithm 2SBound. Finally, our experiments show that RoundTripRank and RoundTripRank+ are robust over various ranking tasks, and 2SBound enables scalable online processing.
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subjects Computational modeling
Educational institutions
Joining processes
MIMICs
Teleportation
Uniform resource locators
title RoundTripRank: Graph-based proximity with importance and specificity?
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