Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
ACM Computing Surveys (CSUR)
Symbolic and numerical regression: experiments and applications
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Unified framework for fast exact and approximate search in dissimilarity spaces
ACM Transactions on Database Systems (TODS)
Analyzing Metric Space Indexes: What For?
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
Signature Quadratic Form Distance
Proceedings of the ACM International Conference on Image and Video Retrieval
On nonmetric similarity search problems in complex domains
ACM Computing Surveys (CSUR)
Ptolemaic indexing of the signature quadratic form distance
Proceedings of the Fourth International Conference on SImilarity Search and APplications
On fast non-metric similarity search by metric access methods
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Algorithmic exploration of axiom spaces for efficient similarity search at large scale
SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
Universal indexing of arbitrary similarity models
Proceedings of the VLDB Endowment
| Hi-index | 0.00 |
The increasing amount of available unstructured content introduced a new concept of searching for information - the content-based retrieval. The principle behind is that the objects are compared based on their content which is far more complex than simple text or metadata based searching. Many indexing techniques arose to provide an efficient and effective similarity searching. However, these methods are restricted to a specific domain such as the metric space model. If this prerequisite is not fulfilled, indexing cannot be used, while each similarity search query degrades to sequential scanning which is unacceptable for large datasets. Inspired by previous successful results, we decided to apply the principles of genetic programming to the area of database indexing. We developed the GP-SIMDEX which is a universal framework that is capable of finding precise and efficient indexing methods for similarity searching for any given similarity data. For this purpose, we introduce the inequality symbolic regression principle and show how it helps the GP-SIMDEX Framework to find appropriate results that in most cases outperform the best-known indexing methods.