The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Substructure similarity search is to retrieve graphs that approximately contain a given query graph. It has many applications, e.g., detecting similar functions among chemical com...
Most similarity search techniques map the data objects into some high-dimensional feature space. The similarity search then corresponds to a nearest-neighbor search in the feature...
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing ...
In recent years, many data mining methods have been proposed for finding useful and structured information from market basket data. The association rule model was recently propos...
There are abundant scenarios for applications of similarity search in databases where the similarity of objects is defined for a subset of attributes, i.e., in a subspace, only. Wh...
Thomas Bernecker, Tobias Emrich, Franz Graf, Hans-...
Similarity search and similarity join on strings are important for applications such as duplicate detection, error detection, data cleansing, or comparison of biological sequences....
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
We consider the use of wavelet transformations as a dimensionality reduction technique to permit efficient similarity search over high-dimensional time-series data. While numerou...
Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...