Fast incremental SimRank on link-evolving graphs
- Submitting institution
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The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 12490
- Type
- E - Conference contribution
- DOI
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10.1109/ICDE.2014.6816660
- Title of conference / published proceedings
- 2014 IEEE 30th International Conference on Data Engineering
- First page
- 304
- Volume
- -
- Issue
- -
- ISSN
- 1063-6382
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- 22
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published at a leading conference in databases and supported by an ARC Discovery Grant, this work won the 2014 CSiRA Best Paper Award. It proposed a new time-efficient similarity search algorithm that utilises the sparsity of real-world graphs to incrementally capture proximities where the edges of the graph are presented as a stream. This research has inspired follow-on work on larger graphs (Bin Cui, Peking University), and has impacted local graph clustering (Michael, UC Berkeley), event-based information organization (James, UMass), and representation learning on networks (Jure, Stanford).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -