Vlastislav Dohnal
Pavel Zezula
Abstract
Similarity is a central notion throughout human lives and it will soon become the prevalent strategy for dealing with digital content also in computer systems. But the exponential growth of data makes the scalability and performance issues serious matters of concern. Contemporary decentralized media of mass communication allowing cooperative and collaborative practices enable users autonomously contribute to production of global media, whose elements are in fact related by numerous multi-facet links of similarity. As an example, consider the sites like Flickr, YouTube, or Facebook that host user-contributed heterogeneous content for a variety of events. Accordingly, the core ability of future data processing systems is the similarity management of large and ever growing volumes of data. In a simplified way, the real-life performance can be constrained from two points of view: (1) the query response time, and (2) the query execution throughput, i.e. the number of queries processed per a unit of time. Typically, the query response time should be on-line, say less than one second, but the query execution throughput can even be expected in hundreds or thousands in case of large-scale web applications.
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Digital Library
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Index Terms
- Real-life performance of metric searching
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