Algorithms for Large Scale Data Analysis
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (15 February 2020) | Viewed by 8326
Special Issue Editor
Interests: design and analysis of randomized algorithms and probabilistic analysis; spectral graph theory and graph clustering; algorithms for large scale data analysis; algorithmic modelling of complex systems
Special Issue Information
Dear Colleagues,
We invite submission of papers describing original and solid research on algorithmic aspects of information retrieval and data mining over large, or very large, datasets. Topics can range from theoretical foundations to novel algorithmic approaches to tackle data mining problems arising in science, business, medicine, and engineering, when data size is an important issue in practice. In particular, we welcome contributions that are methodologically solid, supporting proposed approaches through a sound theoretical and/or experimental analysis, on scenarios of practical relevance. We also welcome application-oriented papers that make innovative technical contributions to research. Authors are explicitly discouraged from submitting incremental results that do not provide any significant advances over existing approaches.
The aim of this Special Issue is to present recent contributions of practical relevance from these areas, as well as contributions investigating the more theoretical aspects of large-scale data analysis.
Topics include but are not limited to the following areas:
- Large-scale information retrieval systems;
- Algorithmic and statistical techniques for big data analysis;
- Large-scale collaborative filtering;
- Algorithms for large-scale graph analysis;
- Large-scale machine learning and optimization;
- Algorithms and tools for distributed data mining (e.g., map reduction);
- Streaming algorithms;
- Applications of large-scale data analysis.
Guest Editor
Manuscript Submission Information
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