Concentric Software, Inc.

Leomart Reyes Crisostomo

Shankar Subramaniam

Madhusudana Shashanka

Bonnie Arogyam Varghese

Sumeet Khirwal

Pankaj Kumar Gupta

Embodiments herein disclose a method for managing at least one document by an electronic device. The method includes receiving at least one document in an electronic form, where the document includes a plurality of content. Further, the method includes determining at least one semantic category associated with the document and a metadata associated with the document. Further, the method includes embedding custom data within the at least one document, where the custom data comprises the at least one of the semantic category associated with the at least one document. Further, the method includes determining at least one among privacy persona and classification label of the document based on the semantic category associated with the document and the metadata associated with the document. Further, the method includes determining access to the document based on at least one among the privacy persona and the classification label of the document.

Method and electronic device for managing sensitive data based on semantic categorization

Embodiments herein disclose a method for determining at least one semantic category of at least one document using an electronic device. The method includes receiving at least one document embedding indicating a semantic representation of at least one document. Further, the method includes determining a probable set of semantic categories of a plurality of semantic categories associated with the document embedding based on an execution of the at least one document embedding on a plurality of proto-models. Further, the method includes receiving the semantic model associated with each of the probable set of semantic categories. Further, the method includes executing the at least one document embedding on the received semantic model. Further, the method includes determining the at least one semantic category out of the probable set of semantic categories, of the at least one document embedding based on the at least one executed document.

Method and electronic device to assign appropriate semantic categories to documents with arbitrary granularity

Methods and systems for optimizing grouping for enhanced access control and risk mitigation. The method includes obtaining user data including data associated with a plurality of users and a plurality of groups, and access data including data associated with a plurality of data objects and corresponding access information. The method includes determining a first mapping information between each of the plurality of groups with corresponding users of the plurality of users based on the user data, and determining a second mapping information between each of the plurality of data objects with corresponding users of the plurality of users based on the access data. The method includes generating a cluster dataset representing a plurality of clusters based at least on processing of a relational structure between the first mapping information and the second mapping information. The plurality of clusters represent newly generated groups of the plurality of users.

Methods and systems for optimizing grouping for enhanced access control and risk mitigation in an enterprise

Embodiments herein disclose a method for managing at least one document by an electronic device. The method includes receiving, by the electronic device, at least one document in an electronic form, where the document includes a plurality of content. Further, the method includes determining at least one semantic category associated with the document and a metadata associated with the document. Further, the method includes determining at least one among privacy persona and classification label of the document based on the semantic category associated with the document and the metadata associated with the document. Further, the method includes determining access to the document based on at least one among the privacy persona and the classification label of the document.

Methods and systems for clustering documents according to semantic similarity are disclosed. The method includes generating an embedding for each of a plurality of documents to form a plurality of embeddings. Each embedding is indicative of a semantic representation for the corresponding document. The method includes segregating the plurality of embeddings into a plurality of shards. The method includes clustering one or more embeddings within each shard of the plurality of shards into the one or more first clusters. The one or more first clusters for each shard collectively constitute a plurality of first clusters. The method includes generating a plurality of second clusters across the plurality of shards, based, at least in part, on semantic similarity between the plurality of embeddings and the plurality of first clusters.

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Sunnyvale, CA, United States of America

Leomart Reyes Crisostomo