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Leaders - Subleaders: An efficient hierarchical clustering algorithm for large data sets
TLDR
An efficient hierarchical clustering algorithm suitable for large data sets is proposed for effective clustering and prototype selection for pattern classification. Expand
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Tree structure for efficient data mining using rough sets
TLDR
We propose a novel data structure, pattern count tree (PC-tree), that can be built by scanning the database only once and use it for efficient and effective rough classification. Expand
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Present and prospective role of bioenergy in regional energy system
Bioenergy is the energy released from the reaction of organic carbon material with oxygen. The organic material derived from plants and animals is also referred to as biomass. Biomass is a flexibleExpand
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End use efficiencies in the domestic sector of Uttara Kannada District
End use efficiency experiments conducted in some households of Masur village (based on 4 days experiment) of Kumta taluk show that there is scope for saving 27-42% of energy by switching to improvedExpand
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An efficient incremental protein sequence clustering algorithm
TLDR
An efficient incremental clustering algorithm, 'leaders-subleaders', an extension of the leader algorithm, suitable for protein sequences of bioinformatics, is proposed for effective clustering. Expand
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Optimum Load Shedding Through Programming Techniques
TLDR
We obtain a new accurate model for sensitivity in power systems and uses it in conjunction with linear programming for the solution of load-shedding problems with a minimum loss of loads. Expand
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Scalable, Distributed and Dynamic Mining of Association Rules
TLDR
We propose a novel pattern tree called Pattern Count tree (PC-tree) which is a complete and compact representation of the database. Expand
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Knowledge-based association rule mining using AND-OR taxonomies
TLDR
We introduce a knowledge-based approach to mine generalized association rules which is sound and interactive. Expand
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Efficient clustering of large data sets
TLDR
Clustering is an activity of finding abstractions from data and these abstractions can be used for decision making . Expand
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