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US 11,379,534 B2Granted
Document feature repository management
AssigneeInternational Business Machines Corporation
InventorsKun Yan Yin, Qi Y Wang, Wen Wang, Hai Ji, Rui W W Wang
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Abstract
A plurality of documents is received. From one or more documents within the plurality, a set of image features is extracted. A document feature repository is generated by storing one or more sets of image features, by document. A document search query is received. The document search query is pre-processed to generate a set of variable document search queries. The document feature repository is searched using the set of variable document search queries. The search results are presented to a user.
Claims20
A method for generating and searching a document feature repository, the method comprising:
- receiving a plurality of documents;
- extracting a set of image features from one or more documents within the plurality of documents, wherein extracting the set of image features comprises:
- parsing the one or more documents into a set of page images, by document;
- generating one or more sets of character blocks for each page image within the set of page images;
- extracting a plurality of character block features for each character block;
- generating the document feature repository by storing the one or more sets of image features, by document;
- receiving a document search query;
- pre-processing the document search query to generate a set of variable document search queries;
- searching the document feature repository using the set of variable document search queries wherein searching the document feature repository using the set of variable document search queries further comprises generating a set of match scores between each set within the plurality of character block features and the set of variable document search queries, wherein generating a set of match scores between the one or more documents and the set of variable document search queries further comprises:
- generating, using Fast Library for Approximate Nearest Neighbors (FLANN), a set of weighted match scores between the plurality of character block features for each of the one or more documents and the set of variable document search queries;
- and
- combining the set of weighted match scores to generate the match score for each of the one or more documents;
- and
- presenting the search results to a user.
11 more elements
A computer program product for generating and searching a document feature repository, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to:
- receive a plurality of documents;
- extract a set of image features from one or more documents within the plurality of documents, wherein extracting the set of image features comprises:
- parsing the one or more documents into a set of page images, by document;
- generating one or more sets of character blocks for each page image within the set of page images;
- extracting a plurality of character block features for each character block;
- generate the document feature repository by storing the one or more sets of image features, by document;
- receive a document search query;
- pre-process the document search query to generate a set of variable document search queries;
- search the document feature repository using the set of variable document search queries, wherein searching the document feature repository using the set of variable document search queries further comprises generating a set of match scores between each set within the plurality of character block features and the set of variable document search queries, wherein generating a set of match scores between the one or more documents and the set of variable document search queries further comprises:
- generating, using Fast Library for Approximate Nearest Neighbors (FLANN), a set of weighted match scores between the plurality of character block features for each of the one or more documents and the set of variable document search queries;
- and
- combining the set of weighted match scores to generate the match score for each of the one or more documents;
- and
- present the search results to a user.
11 more elements
A system for generating and searching a document feature repository, comprising:
- a memory with program instructions included thereon;
- and
- a processor in communication with the memory, wherein the program instructions cause the processor to:
- receive a plurality of documents;
- extract a set of image features from one or more documents within the plurality of documents, wherein extracting the set of image features comprises:
- parsing the one or more documents into a set of page images, by document
- generating one or more sets of character blocks for each page image within the set of page images;
- extracting a plurality of character block features for each character block;
- generate the document feature repository by storing the one or more sets of image features, by document;
- receive a document search query;
- pre-process the document search query to generate a set of variable document search queries;
- search the document feature repository using the set of variable document search queries, wherein searching the document feature repository using the set of variable document search queries further comprises generating a set of match scores between each set within the plurality of character block features and the set of variable document search queries, wherein generating a set of match scores between the one or more documents and the set of variable document search queries further comprises:
- generating, using Fast Library for Approximate Nearest Neighbors (FLANN), a set of weighted match scores between the plurality of character block features for each of the one or more documents and the set of variable document search queries;
- and
- combining the set of weighted match scores to generate the match score for each of the one or more documents;
- and
- present the search results to a user.
14 more elements
Dependencies are inferred from the claim text.