Method and system for building entity hierarchy from big data

Abstract

The various embodiments herein provide a method and a system for building an entity hierarchy. The method comprises extracting a plurality of entities from a bin data, determining a parent entity by understanding a context in which the entity is used, resolving the entities by bringing the synonymous entities together and holding the polysemous entities apart based on a semantic context and a syntactic context and building a hierarchical structure of entities using knowledge repositories, ontologies and language repositories along with natural language processing techniques. The method of extracting entities from the structured data comprises identifying each data point as an entity and identifying entities based on a relationship defined with other entities. The method of extracting entities from unstructured data includes a self-learning process and training based learning process to learn new parent entities from domain specific documents using new entity recognition models.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]The present application claims priority of Indian provisional application serial number 3286 / CHE / 2012 filed on Aug. 10, 2012, and that application is incorporated in its entirety at least by reference.BACKGROUND[0002]1. Technical Field[0003]The embodiments herein generally relate to data mining and particularly relates to extracting and resolving entities from a large collection of data. The embodiments herein more particularly relates to a method and system for extracting entities from big data and building an entity hierarchy using language and domain models.[0004]2 Description of the Related Art[0005]A big data is a large collection, of information which derives its data content from plurality of structured, unstructured and semi-structured data sources. The big data requires a paradigm shift in the way the data is looked at in the past. The data cannot anymore reside in pockets and not talk each other. It is imperative that all of it t...

AI Technical Summary

Benefits of technology

The patent aims to offer a method and system for making accurate and effective queries with respect to entities. The technical effects of the patent text are improving the efficiency and accuracy of pattern queries related to entities.

Problems solved by technology

The challenge of figuring out entities is tough one for several reasons as many entities exist only in richly varied forms.

Therefore the current systems are limited by the relationships that exist between named entities and never consider the relationship between concepts or a concept and a named entity.

The existing data analysis and information extraction techniques are usually designed to target at a particular media type and not applicable to data generated by a different media type.

Further, the existing literature does not bring in domain ontologies and knowledge bases for semantic resolution in the context of entity extraction.

Images