Scalable Similarity Search for Big Data - Challenges and Research Objectives.
Infoscale(2015)
摘要
Analysis of contemporary Big Data collections require an
effective and efficient content-based access to data which is
usually unstructured. This first implies a necessity to uncover
descriptive knowledge of complex and heterogeneous objects to
make them findable. Second, multimodal search structures are
needed to efficiently execute complex similarity queries
possibly in outsourced environments while preserving privacy.
Four specific research objectives to tackle the challenges are
outlined and discussed. It is believed that a relevant solution
of these problems is necessary for a scalable similarity search
operating on Big Data.
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关键词
Big data, Scalability, Information retrieval, Similarity search, Findability, Data outsourcing, Data privacy, Information extraction
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