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| Content Provider | ACM Digital Library |
|---|---|
| Author | Tian, Boyu Xiao, Xiaokui |
| Abstract | SimRank is a similarity measure for graph nodes that has numerous applications in practice. Scalable SimRank computation has been the subject of extensive research for more than a decade, and yet, none of the existing solutions can efficiently derive SimRank scores on large graphs with provable accuracy guarantees. In particular, the state-of-the-art solution requires up to a few seconds to compute a SimRank score in million-node graphs, and does not offer any worst-case assurance in terms of the query error. This paper presents SLING, an efficient index structure for SimRank computation. SLING guarantees that each SimRank score returned has at most ε additive error, and it answers any single-pair and single-source SimRank queries in O(1/ε) and O(n/ε) time, respectively. These time complexities are near-optimal, and are significantly better than the asymptotic bounds of the most recent approach. Furthermore, SLING requires only O(n/ε) space (which is also near-optimal in an asymptotic sense) and O(m/ε + n log $n/δ/ε^{2})$ pre-computation time, where δ is the failure probability of the preprocessing algorithm. We experimentally evaluate SLING with a variety of real-world graphs with up to several millions of nodes. Our results demonstrate that SLING is up to 10000 times (resp. 110 times) faster than competing methods for single-pair (resp. single-source) SimRank queries, at the cost of higher space overheads. |
| Starting Page | 1859 |
| Ending Page | 1874 |
| Page Count | 16 |
| File Format | |
| ISBN | 9781450335317 |
| DOI | 10.1145/2882903.2915243 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-06-26 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Simrank Query processing Graphs Approximate algorithm Indexing |
| Content Type | Text |
| Resource Type | Article |
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