Partitioned posting files: a parallel inverted file structure for information retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Inverted files versus signature files for text indexing
ACM Transactions on Database Systems (TODS)
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Inverted files for text search engines
ACM Computing Surveys (CSUR)
Effective Proximity Retrieval by Ordering Permutations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate similarity search in metric spaces using inverted files
Proceedings of the 3rd international conference on Scalable information systems
Approximate similarity search: A multi-faceted problem
Journal of Discrete Algorithms
Speeding Up Permutation Based Indexing with Indexing
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
MiPai: Using the PP-Index to Build an Efficient and Scalable Similarity Search System
SISAP '09 Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
A Brief Index for Proximity Searching
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Similarity Search: The Metric Space Approach
Similarity Search: The Metric Space Approach
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We present parallel strategies for indexing and searching permutation-based indexes for high dimensional data using inverted files. In this paper, three strategies for parallelization are discussed; posting lists decomposition, reference points decomposition, and multiple independent inverted files. We study performance, efficiency, and effectiveness of our strategies on high dimensional datasets of millions of images. Experimental results show a good performance compared to the sequential version with the same efficiency and effectiveness.