Abstract: A system and a method for classifying sensitive data elements in a file is provided. The method includes receiving and converting, the unstructured data file into a machine-readable format and generating, a plurality of sensitive data features. The plurality of sensitive data features represents single element of the sensitive data. The method includes generating, a plurality of adjacent elements corresponding to the single elements of the sensitive data and generating a plurality of feature categories. The method includes aggregating, the plurality of adjacent node features and the plurality of edge features. The method includes calculating and concatenating the plurality of aggregated adjacent nodes features and the plurality of aggregated edge features. The method includes comparing, the distance of the sensitive data from all of the adjacent sensitive data. The method includes classifying and predicting, the sensitive data to be a true positive or false positive sensitive data by using machine learning.

Abstract: A system and a method for entity resolution is disclosed. An entity reference parsing subsystem to parse one or more entity references of a corresponding seed set of entity into corresponding one or more personal data properties and property values. A property value standardization subsystem performs one or more standardization operations for standardization of the corresponding one or more property values. A property value anonymization subsystem secures the one or more property values by performing one or more anonymization procedures. A property strength quantification subsystem identifies at least one additional property suspected to belong to the seed set of the entity, assigns a property strength score to the at least one additional property, adds the at least one additional property to the corresponding seed set of entity. A local entity resolution and a global entity resolution subsystem performs a first and a second entity resolution process respectively.

Abstract: A system for association of data elements within a document is disclosed. An input data receiving subsystem receives an input data source of the document. A feature generation subsystem obtains one or more lists of personal data, generates one or more personal data features representing a relationship between one or more personal data elements. An affinity computation subsystem assesses each of the one or more personal data features, computes affinity score between the one or more personal data elements, generates one or more affinities. A personal data relationship identification subsystem assigns the one or more personal data elements to corresponding one or more identification stages, derives a set of identities corresponding to the one or more personal data elements. An identity filtration subsystem receives the one or more affinities and the set of identities, determines a validation of the set of identities, filters out the set of identities.