Optimizing metric access methods for querying and mining complex data types
There are several application scenarios that can take advantage from the efficient processing of similarity operations in complex data types, such as multimedia data. Among them, it is possible to mention the execution of more complex query types (e.g., similarity queries) and several well-known data mining algorithms (e.g., data clustering) that are directly based on similarity computations. In order to speed up the similarity-based comparisons performed by these approaches, it is possible to store the dataset in specialized data structures known as metric access methods (MAM).
metric access methods similarity queries data mining multimedia indexing