Sparse embedding index for search
AssigneeAdobe Inc.
InventorsTung Mai, Saayan Mitra, Ryan A. Rossi, Gaurav Gupta, Anup Rao, Xiang Chen
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AssigneeAdobe Inc.
InventorsTung Mai, Saayan Mitra, Ryan A. Rossi, Gaurav Gupta, Anup Rao, Xiang Chen
Estimating the term…
A search system facilitates efficient and fast near neighbor search given item vector representations of items, regardless of item type or corpus size. To index an item, the search system expands an item vector for the item to generate an expanded item vector and selects elements of the expanded item vector. The item is index by storing an identifier of the item in posting lists of an index corresponding to the position of each selected element in the expanded item vector. When a query is received, a query vector for the item is expanded to generate an expanded query vector, and elements of the expanded query vector are selected. Candidate items are identified based on posting lists corresponding to the position of each selected element in the expand query vector. The candidate items may be ranked, and a result set is returned as a response to the query.
One or more computer storage media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform operations, the operations comprising:
A computerized method comprising:
A computer system comprising:
Dependencies are inferred from the claim text.