Method and system for recommending products to consumers by induction of decision trees
First Claim
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1. A computer implemented method for recommending a product to a consumer, comprising the steps of:
- representing a purchasing history of a consumer as an adjacency lattice;
extracting training examples from the adjacency lattice;
constructing a decision tree using the training examples;
reducing a size of the decision tree to a reduced size decision tree; and
searching the reduced size decision tree for a recommendation of a product to the consumer.
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Abstract
A method and system recommend a product to a consumer. A purchasing history of a consumer is represented by an adjacency lattice stored in a memory. Training examples are extracted from the adjacency lattice, and a decision tree is constructed using the training examples. A size of the decision tree is reduced, and the reduced size decision tree is searched for a recommendation of a product to the consumer.
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Citations
9 Claims
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1. A computer implemented method for recommending a product to a consumer, comprising the steps of:
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representing a purchasing history of a consumer as an adjacency lattice;
extracting training examples from the adjacency lattice;
constructing a decision tree using the training examples;
reducing a size of the decision tree to a reduced size decision tree; and
searching the reduced size decision tree for a recommendation of a product to the consumer. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for recommending a product to a consumer, comprising the steps of:
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a memory configured to store an adjacency lattice representing a purchasing history of a consumer;
means for extracting training examples from the adjacency lattice;
means for constructing a decision tree using the training examples;
means for reducing a size of the decision tree to a reduced size decision tree; and
means for searching the reduced size decision tree for a recommendation of a product to the consumer. - View Dependent Claims (9)
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Specification