Though searching is already the most frequently used application of information technology today, similarity approach to searching is increasingly playing more and more important role in construction of new search engines. In the last twenty years, the technology has matured and many centralized, distributed, and even peer-to-peer architectures have been proposed. However, the use of similarity searching in numerous potential applications is still a challenge. In the talk, four research directions in developing similarity search applications at Masaryk University DISA laboratory are to be discussed. First, we concentrate on accelerating large-scale face recognition applications and continue with generic image annotation task for retrieval purposes. In the second half, we focus on data stream processing applications and finish the talk with the ambition topic of content-based retrieval in human motion-capture data. Applications will be illustrated by online prototype implementations.
CITATION STYLE
Zezula, P. (2016). Similarity searching for database applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9809 LNCS, pp. 3–10). Springer Verlag. https://doi.org/10.1007/978-3-319-44039-2_1
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