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US 11,599,666 B2Granted
Smart document migration and entity detection
AssigneeSap SE
InventorsShiva Prasad Nayak, Srinivas Rao, Anahita Minuchaher Havewala, Suresh Pasumarthi
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AssigneeSap SE
InventorsShiva Prasad Nayak, Srinivas Rao, Anahita Minuchaher Havewala, Suresh Pasumarthi
Estimating the term…
Systems and methods include extraction of a plurality of clauses from each of a plurality of electronic documents, determination, for each of the plurality of clauses and using a machine-learned algorithm, an associated clause type, identification of one or more data privacy protection entities present within each of one or more of the plurality of clauses, determination, for each of the one or more of the plurality of clauses, of a weighted frequency for each of the one or more data privacy protection entities present within the clause based on a type of the data privacy protection entity, determination of a weighted frequency associated with each of the plurality of electronic documents based on the determined weighted frequency for each of the one or more data privacy protection entities present within clauses of the plurality of electronic documents, and storage of an identifier of each of the plurality of electronic documents in association with a respective determined weighted frequency.
A system comprising:
A computer-implemented method comprising:
A non-transitory computer-readable medium storing processor-executable process steps executable by a processing unit of a computing system to cause the computing system to:
Dependencies are inferred from the claim text.
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To a system of files or objects, e.g. local or distributed file system or database: protecting personal data, e.g. for financial or medical purposes
Of unstructured textual data: clustering; Classification
Details of database functions independent of the retrieved data types: document management systems
Recurrent networks, e.g. Hopfield networks: characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
About 14 years 8 months of term left · ends 24 Jun 2041 (estimated)
The present application claims priority to Indian Provisional Application No. 202011022212, filed May 27, 2020, and incorporates said Indian Provisional Application by reference for all purposes.
Modern database systems store vast amounts of data for their respective enterprises. The data may include transactional data, master data, unstructured data and other data. The use and re-use of such data is an intergral aspect of enterprise operations.
The data may represent documents such as, for example, legal contracts. Existing hardcopies of documents may be scanned and stored into database systems, but such scanning fails to preserve any substantive or semantic information embodied within the documents. The documents, or selected portions thereof, cannot therefore efficiently be used or re-used by users of such systems. What is needed are systems to efficiently load physical documents into a document management system in a manner that detects semantic information associated with various document portions and allows for independent re-use of such portions as well as electronic access to the content of the original documents.
FIG. 1 is a block diagram of an overall architecture according to some embodiments.
FIG. 2 is a block diagram of an architecture to train an artificial neural network to classify document clauses according to some embodiments.
FIG. 3 is a block diagram of a system to classify and index document clauses according to some embodiments.
The following description is provided to enable any person in the art to make and use the described embodiments and sets forth the best mode contemplated for carrying out some embodiments. Various modifications, however, will be readily-apparent to those in the art.
Briefly, some embodiments operate to input hardcopies of document, identify clauses within the documents, classify the clauses by type, and tag each clause with metadata identifying its type, associated document, and order within its associated document. Such information may be used to recreate the documents electronically, and also by a document editor to identify clauses to utilize as templates during creation of a new document.
Some embodiments operate to efficiently identify DPP entities within a set of electronic documents, generate a document index to associate the documents with their constituent DPP entities and clause-specific DPP weightings, and generate DPP weight-based dependency relation graphs between named entities and associated documents/clauses/DPP entities.