Similarity Search: The Metric Space ApproachSpringer Science & Business Media, 7 jun 2006 - 220 páginas 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 and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology. |
Índice
Overview | 3 |
Basic Partitioning Principles | 20 |
Policies for Avoiding Distance Computations | 26 |
Metric Space Transformations | 35 |
Approximate Similarity Search | 41 |
Advanced Issues | 50 |
SURVEY OF EXISTING APPROACHES | 67 |
3 | 78 |
5 | 95 |
Overview 103 | 101 |
APPROXIMATE SIMILARITY SEARCH | 145 |
PARALLEL AND DISTRIBUTED INDEXES 161 | 160 |
Concluding Summary | 193 |
99 | 206 |
211 | |
Abbreviations | 219 |
Otras ediciones - Ver todo
Similarity Search: The Metric Space Approach Pavel Zezula,Giuseppe Amato,Vlastislav Dohnal,Michal Batko No hay ninguna vista previa disponible - 2010 |
Similarity Search: The Metric Space Approach Pavel Zezula,Giuseppe Amato,Vlastislav Dohnal,Michal Batko No hay ninguna vista previa disponible - 2005 |
Términos y frases comunes
ACM Press applied approximate nearest neighbor approximate similarity search ball regions buckets accessed bulk-loading algorithm Chapter cluster covering radius D-index data objects dataset defined distance computations distance d(q distance distribution distance function Dohnal edit distance efficiency entry evaluation example exclusion bucket exclusion set Figure index structure insertion algorithm internal node International Conference iter key dimension leaf node lower bound M-tree messages metric space metric tree nearest neighbor queries nearest neighbor search NNID number of distance number of objects object q overlap pair parallel cost parameter Patella peer performance priority queue Proceedings processing proximity qualifying objects query execution query object query region radii range query range search relative error result-set retrieved scalability search algorithm search costs search in metric search radius Section separable sets similarity queries specific split functions stop condition stored strategy subsets subtree technique tree values vector space Zezula