METHOD AND SYSTEM FOR MODELING DATA

• US 20130117316A1
• Filed: 04/27/2012
• Published: 05/09/2013
• Est. Priority Date: 05/16/2011
• Status: Active Grant

• Current Assignee: Xurmo Technologies Pvt Ltd.
• Original Assignee: Xurmo Technologies Pvt Ltd.
• Inventors: Gopalakrishnan, Sridhar
• Granted Patent: US 8,725,754 B2
• Time in Patent Office: Days
• US Class Current: 707/790
• CPC Class Codes: G06F 16/288 Entity relationship models

Abstract

The various embodiments herein provide a method and system for modeling a data. The method for modeling data comprises steps of extracting the data from a plurality of data sources, identifying a plurality of entities from the plurality of data, defining occurrence of a relationship between the plurality of entities, capturing recurrences of the relationship between the plurality of entities based on one or more common interactions between the plurality of entities and creating a data model indicating the occurrences and recurrences of the relationship between the plurality of the entities. The data model is adapted to store data corresponding to the plurality of entities, the relationship between the plurality of entities and the common interactions between the plurality of entities. The plurality of entities includes contents of a digital data artifact.

Claims

1. A method for modeling data, the method comprises:

extracting the data from a plurality of data sources;

identifying a plurality of entities from the plurality of data;

defining occurrence of a relationship between the plurality of the entities;

capturing recurrences of the relationship between the plurality of entities based on one or more common interactions between the plurality of entities; and

creating a data model indicating the occurrences and recurrences of the relationship between the plurality of the entities;

wherein the data model is adapted to store data corresponding to the plurality of entities, the relationship between the plurality of entities and the common interactions between the plurality of entities.

2. The method of claim 1, further comprises updating the data model automatically in response to a modification in a context information or an operation history which is associated with at least one of the plurality of entities.

3. The method of claim 1, further comprises qualifying the occurrence of the relationship between the pluralities of entities based on a time frame.

4. The method of claim 1, further comprising defining one or more entities associated with the plurality of entities based on independent existence of the data across the plurality of entities.

5. The method of claim 1, wherein each of the plurality of the entities is connected to other entity by a relationship, where each relationship functions as an entity.

6. The method of claim 1, wherein capturing the recurrence of the relationship comprises:

identifying the data based on a history of one or more interactions between the plurality of entities;

detecting one or more entities which are commonly found with respect to recurrence of relationship; and

ascertaining the relevancy of the data by evaluating multiple occurrence of the relationship between the plurality of entities.

7. The method of claim 1, wherein the plurality of data sources comprises at least one of emails, document management systems, database management systems, data warehouses and a plurality of public domain data sources;

wherein the data sources include structured data sources such as databases, semi-structured data sources and unstructured data sources such as emails.

8. The method of claim 1, wherein the plurality of entities includes contents of a digital data artifact.

9. The method of claim 1, wherein the plurality of entities is of a type including at least one of a known entity and a derived entity.

10. The method of claim 1, wherein a strength of the plurality of entities is determined based on an identification of a credibility of the data sources.

11. A system for modeling a data , the system comprising:

a data extractor module to extract the data from a plurality of data sources;

an entity extractor to define a plurality of entities;

a relationship identifier to identify occurrence of a relationship between the plurality of entities and to evaluate recurrences of the relationship between the plurality of the entities; and

a data model generator for creating a data model;

wherein the data model stores a data corresponding to the plurality of entities, occurrence of the relationship between the plurality of entities and recurrences of the relationships between the plurality of entities based on one or more common interactions between the plurality of entities.

12. The system of claim 11, further comprising a datastore implemented using one or more data structures;

wherein then data structures are adapted to interact with each other for optimization of the data.

13. The system of claim 11, wherein the a relationship identifier is adapted to evolve the relationships between the plurality of entities based on at least one a strength, a context and a frequency of the common interactions between the plurality of entities over a time frame.

14. The system of claim 11, wherein the entity extractor is adapted to:

automatically extract a document metadata from a plurality of text structured, and semi-structured and unstructured text documents; and

extract a structured information from a plurality of unstructured machine readable documents and semi-structured machine readable documents.

15. The system of claim 11, wherein the relationship identifier includes one or more machine learning algorithms to evaluate occurrence and recurrences of relationships between the plurality of the entities.

16. The system of claim 11, wherein the data model is adapted to be programmed through an application programming interface to employ a user defined data logic.