Search clustering
First Claim
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1. A method comprising:
- identifying noise data using a demand factor that is based on relationships of items and categories to query terms of search queries;
retrieving, from a plurality of listings, item data that is filtered from the noise data based on the demand factor;
constructing, using a processor of a machine, at least one base cluster having at least one document with common item data stored in a suffix ordering;
compacting the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst clusters; and
merging the compacted cluster representation to generate a merged cluster based upon a first overlap value applied to the at least one document with common item data.
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Abstract
In one example embodiment, a method is illustrated as including retrieving item data from a plurality of listings, the item data filtered from noise data, constructing at least one base cluster having at least one document with common item data stored in a suffix ordering, compacting the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst the clusters, and merging the compacted cluster representation to generate a merged cluster, the merging based upon a first overlap value applied to the at least one document with common item data.
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Citations
20 Claims
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1. A method comprising:
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identifying noise data using a demand factor that is based on relationships of items and categories to query terms of search queries; retrieving, from a plurality of listings, item data that is filtered from the noise data based on the demand factor; constructing, using a processor of a machine, at least one base cluster having at least one document with common item data stored in a suffix ordering; compacting the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst clusters; and merging the compacted cluster representation to generate a merged cluster based upon a first overlap value applied to the at least one document with common item data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system comprising:
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a processor of a machine; a demand data engine to identify noise data using a demand factor that is based on relationships of items and categories to query terms of search queries; a retrieving engine to retrieve, from a plurality of listings, item data that is filtered from the noise data based on the demand factor; a cluster generator to construct, using the processor, at least one base cluster having at least one document with common item data stored in a suffix ordering; a compacting engine to compact the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst clusters; and a first merging engine to merge the compacted cluster representation to generate a merged cluster based upon a first overlap value applied to the at least one document with common item data. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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20. A tangible machine-readable storage device comprising instructions, which, when implemented by one or more machines that cause the one or more machines to perform the operations comprising:
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identifying noise data using a demand factor that is based on relationships of items and categories to query terms of search queries; retrieving, from a plurality of listings, item data that is filtered from the noise data based on the demand factor; constructing, using a processor, at least one base cluster having at least one document with common item data stored in a suffix ordering; compacting the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst clusters; and merging the compacted cluster representation to generate a merged cluster based upon a first overlap value applied to the at least one document with common item data.
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Specification