On (not) indexing quadratic form distance by metric access methods
Proceedings of the 14th International Conference on Extending Database Technology
Consensus self-organized models for fault detection (COSMO)
Engineering Applications of Artificial Intelligence
A fast pivot-based indexing algorithm for metric spaces
Pattern Recognition Letters
An affinity-based new local distance function and similarity measure for kNN algorithm
Pattern Recognition Letters
A log square average case algorithm to make insertions in fast similarity search
Pattern Recognition Letters
Image retrieval employing genetic dissimilarity weighting and feature space transformation functions
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Parallel approaches to permutation-based indexing using inverted files
SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
DisC diversity: result diversification based on dissimilarity and coverage
Proceedings of the VLDB Endowment
Cost-aware query planning for similarity search
Information Systems
The impact of motion dimensionality and bit cardinality on the design of 3D gesture recognizers
International Journal of Human-Computer Studies
An efficient access method for multimodal video retrieval
Proceedings of the 19th Brazilian symposium on Multimedia and the web
Discovering common motifs in cursor movement data for improving web search
Proceedings of the 7th ACM international conference on Web search and data mining
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The proliferation of information housed in computerized domains makes it vital to find tools to search these resources efficiently and effectively. Ordinary retrieval techniques are inadequate because sorting is simply impossible. Consequently, proximity searching has become a fundamental computation task in a variety of application areas. Similarity Search focuses on the state of the art in developing index structures for searching the metric space. Part I of the text describes major theoretical principles, and provides an extensive survey of specific techniques for a large range of applications. Part II concentrates on approaches particularly designed for searching in large collections of data. After describing the most popular centralized disk-based metric indexes, approximation techniques are presented as a way to significantly speed up search time at the cost of some imprecision in query results. Finally, the scalable and distributed metric structures are discussed.