With an exponential increase in the provisioning of multimedia devices over the Internet of
Things (IoT), a significant amount of multimedia data (also referred to as multimedia big data …

The area of similarity searching is a very hot topic for both research and c-mercial
applications. Current data processing applications use data with c-siderably less structure …

Nearest-Neighbor Methods in Learning and Vision | Guide books skip to main content ACM
Digital Library home ACM Association for Computing Machinery corporate logo Google, Inc …

Searching for approximate nearest neighbors (ANN) in the high-dimensional Euclidean
space is a pivotal problem. Recently, with the help of fast SIMD-based implementations …

Nearest neighbor search and many other numerical data analysis tools most often rely on
the use of the euclidean distance. When data are high dimensional, however, the euclidean …

Content-based copy retrieval (CBCR) aims at retrieving in a database all the modified
versions or the previous versions of a given candidate object. In this paper, we present a …

A method is proposed for indexing spaces with arbitrary distance measures, so as to
achieve efficient approximate nearest neighbor retrieval. Hashing methods, such as locality …

We review the major paradigms for approximate similarity queries and propose a
classification schema that easily allows existing approaches to be compared along several …

We propose an embedding-based framework for subsequence matching in time-series
databases that improves the efficiency of processing subsequence matching queries under …

This paper describes BoostMap, a method for efficient nearest neighbor retrieval under
computationally expensive distance measures. Database and query objects are embedded …