Conference Proceeding Article
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.
Queries, specificity, graphs, random walk, round trip, algorithms, ranking tasks
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
2013 IEEE International Conference on Data Engineering ICDE: 8-12 April, Brisbane, Australia: Proceedings
IEEE Computer Society
City or Country
Los Alamitos, CA
FANG, Yuan; CHANG, Kevin Chen Chuan; and LAUW, Hady W..
RoundTripRank: Graph-based Proximity with Importance and Specificity. (2013). 2013 IEEE International Conference on Data Engineering ICDE: 8-12 April, Brisbane, Australia: Proceedings. 613-624. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1715
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