Monte Carlo methods. Vol. 1: basics
Monte Carlo methods. Vol. 1: basics
Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
The effectiveness of GIOSS for the text database discovery problem
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
A cost model for nearest neighbor search in high-dimensional data space
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Database selection techniques for routing bibliographic queries
Proceedings of the third ACM conference on Digital libraries
Multi-dimensional selectivity estimation using compressed histogram information
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Automatic discovery of language models for text databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient progressive sampling
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Simplified Approach to Image Processing: Classical and Modern Techniques in C
Simplified Approach to Image Processing: Classical and Modern Techniques in C
Using Relevance Feedback in Content-Based Image Metasearch
IEEE Internet Computing
Visually Searching the Web for Content
IEEE MultiMedia
Supporting Ranked Boolean Similarity Queries in MARS
IEEE Transactions on Knowledge and Data Engineering
Data Resource Selection in Distributed Visual Information Systems
IEEE Transactions on Knowledge and Data Engineering
Efficient Color Histogram Indexing for Quadratic Form Distance Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining Text Databases to Search in the Internet
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Server Ranking for Distributed Text Retrieval Systems on the Internet
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Estimating the Usefulness of Search Engines
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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Image databases on the Web have heterogeneous characteristics since they use different similarity measures and queries are processed depending on their own schemes. In the content-based image retrieval from distributed sites, it is crucial that the metaserver has the capability to find objects, similar to a given query object in terms of the global similarity measure, from different image databases with different local similarity measures. In this paper, we investigate the problem of finding databases, which contain more objects relevant to a given query than other databases, from many image databases dispersed on the Web. This problem is referred to as a database selection problem.We propose a new selection method to determine candidate databases. The selection of databases is based on the hybrid estimator using a few sample objects and compressed histogram information of image databases. Extensive experiments on a large number of image data demonstrate that our proposed method improves the effectiveness of distributed content-based retrieval in a heterogeneous environment.