RECOMMENDING KEYWORDS
First Claim
1. A system for recommending keywords, comprising:
- one or more processors configured to;
receive a set of product information including a product title;
extract and parse the product title into a set of parsed elements;
find a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored mappings between parsed data and keywords;
determine a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords;
sort at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and
select a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list; and
one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions.
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Accused Products
Abstract
Recommending keywords is disclosed, including: receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords; sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list.
31 Citations
20 Claims
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1. A system for recommending keywords, comprising:
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one or more processors configured to; receive a set of product information including a product title; extract and parse the product title into a set of parsed elements; find a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored mappings between parsed data and keywords; determine a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords; sort at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and select a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for recommending keywords, comprising:
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receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords; sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A computer program product for recommending keywords, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:
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receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords; sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list.
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Specification