Communications of the ACM
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
Parallel text searching in serial files using a processor farm
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Parallel text retrieval on a high performance supercomputer using the Vector Space Model
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Integrating structured data and text: a relational approach
Journal of the American Society for Information Science
High-quality and high-performance full-text document retrieval: the parallel InfoGuide system
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Document Allocation In Multiprocessor Information Retrieval Systems
Advanced Database Systems
Evolutionary Algorithms for Allocating Data in Distributed Database Systems
Distributed and Parallel Databases
Static and adaptive distributed data replication using genetic algorithms
Journal of Parallel and Distributed Computing
dg.o '05 Proceedings of the 2005 national conference on Digital government research
New theoretical findings in multiple personalized recommendations
Proceedings of the 2010 ACM Symposium on Applied Computing
An evolutionary approach to schema partitioning selection in a data warehouse
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
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We formally define the Multiprocessor Document Allocation Problem (MDAP) and prove it to be computationally intractable (NP Complete). Once it is shown that MDAP is NP Complete, we describe a document allocation algorithm based on genetic algorithms. This algorithm assumes that the documents are clustered using any one of the many clustering techniques. We later show that our allocation algorithm probabilistically converges to a good solution. For a behavioral evaluation, we present sample experimental results.