Unified and incremental SimRank: Index-free approximation with scheduled principle

• Main Authors: ZHU, Fanwei, FANG, Yuan, ZHANG, Kai, CHANG, Kevin C.-C., CAO, Hongtai, JIANG, Zhen, WU, Minghui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: SimRank approximation; unification; index-free; scheduled principle; scalability; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/8209; https://ink.library.smu.edu.sg/context/sis_research/article/9212/viewcontent/TKDE21_UISim.pdf
• Institution: Singapore Management University

SimRank is a popular link-based similarity measure on graphs. It enables a variety of applications with different modes of querying (e.g., single-pair, single-source and all-pair modes). In this paper, we propose UISim, a unified and incremental framework for all SimRank modes based on a scheduled approximation principle. UISim processes queries with incremental and prioritized exploration of the entire computation space, and thus allows flexible tradeoff of time and accuracy. On the other hand, it creates and shares common “building blocks” for online computation without relying on indexes, and thus is efficient to handle both static and dynamic graphs. Our experiments on various real-world graphs show that to achieve the same accuracy, UISim runs faster than its respective state-of-the-art baselines, and scales well on larger graphs.