Conventional research on similarity search focuses on measuring the similarity between objects with the same type. However, in many real-world applications, we need to measure the...
Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie...
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
A new data structure for efficient similarity search in very large datasets of high-dimensional vectors is introduced. This structure called the inverted multi-index generalizes ...
Many binary code encoding schemes based on hashing have been actively studied recently, since they can provide efficient similarity search, especially nearest neighbor search, an...
Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series d...
Thanawin Rakthanmanon, Bilson J. L. Campana, Abdul...
In recent years, both hashing-based similarity search and multimodal similarity search have aroused much research interest in the data mining and other communities. While hashing-...
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
Large collections of 3D models from the same object class (e.g., chairs, cars, animals) are now commonly available via many public repositories, but exploring the range of shape v...
Vladimir G. Kim, Wilmot Li, Niloy J. Mitra, Stephe...
Abstract—Most objects and data in the real world are interconnected, forming complex, heterogeneous but often semistructured information networks. However, many database research...
Aggregate similarity search, a.k.a. aggregate nearest neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects...