PROBABILISTIC RECOMMENDATION OF AN ITEM
First Claim
1. A computer-implemented method of recommending an item to a potential buyer, the method comprising:
- accessing behavior data pertinent to a first cluster of items, the first cluster representing a first product of which each item of the first cluster is a specimen, the behavior data including an event record representative of a first event type pertinent to the first product;
calculating a probability based on the behavior data, the probability being of a co-occurrence of a second event type with the first event type, the second event type pertaining to a second product represented by a second cluster of items, the second cluster including the item to be recommended to the potential buyer, the calculating being performed by a module implemented using a processor of a machine;
identifying the item based on the probability of the co-occurrence; and
presenting a recommendation of the item to the potential buyer, the recommendation including item data descriptive of the item and indicating the item as a specimen of the second product.
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Accused Products
Abstract
A clustering and recommendation machine determines that an item is included in a cluster of items. The machine accesses item data descriptive of the item. The machine accesses a vector that represents the cluster and calculates the likelihood that the item is included in the cluster, based on the item variable and the probability parameter. The machine determines that the item is included in the cluster, based on the likelihood. The machine also recommends an item to a potential buyer. The machine accesses behavior data that represents a first event type pertinent to a first cluster of items. The machine calculates a probability that a second event type pertaining to a second cluster of items will co-occur with the first event type. The machine identifies an item from the second cluster to be recommended and presents a recommendation of the item to the potential buyer.
116 Citations
20 Claims
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1. A computer-implemented method of recommending an item to a potential buyer, the method comprising:
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accessing behavior data pertinent to a first cluster of items, the first cluster representing a first product of which each item of the first cluster is a specimen, the behavior data including an event record representative of a first event type pertinent to the first product; calculating a probability based on the behavior data, the probability being of a co-occurrence of a second event type with the first event type, the second event type pertaining to a second product represented by a second cluster of items, the second cluster including the item to be recommended to the potential buyer, the calculating being performed by a module implemented using a processor of a machine; identifying the item based on the probability of the co-occurrence; and presenting a recommendation of the item to the potential buyer, the recommendation including item data descriptive of the item and indicating the item as a specimen of the second product. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A system to recommend an item to a potential buyer, the system comprising:
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an access module to access behavior data pertinent to a first cluster of items, the first cluster representing a first product of which each item of the first cluster is a specimen, the behavior data including an event record representative of a first event type pertinent to the first product; a hardware-implemented probability module to calculate a probability based on the behavior data, the probability being of a co-occurrence of a second event type with the first event type, the second event pertaining to a second product represented by a second cluster of items, the second cluster including the item to be recommended to the potential buyer; a recommendation module to; identify the item based on the probability of the co-occurrence; and present a recommendation of the item to the potential buyer, the recommendation including item data descriptive of the item and indicating the item as a specimen of the second product. - View Dependent Claims (16, 17)
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18. A machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform a method comprising:
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accessing behavior data pertinent to a first cluster of items, the first cluster representing a first product of which each item of the first cluster is a specimen, the behavior data including an event record representative of a first event type pertinent to the first product; calculating a probability based on the behavior data, the probability being of a co-occurrence of a second event type with the first event, the second event type pertaining to a second product represented by a second cluster of items, the second cluster including an item to be recommended to a potential buyer; identifying the item based on the probability of the co-occurrence; and presenting a recommendation of the item to the potential buyer, the recommendation including item data descriptive of the item and indicating the item as a specimen of the second product. - View Dependent Claims (19, 20)
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Specification