Graph based Question Answering System
This addresses the problem of automated data structuring for text analytics, but appears incremental as it builds on existing graph database approaches.
The paper tackles the challenge of converting unstructured textual data into structured data for analytics by developing a graph-based information extraction and retrieval system, but does not report specific results or numbers.
In today's digital age in the dawning era of big data analytics it is not the information but the linking of information through entities and actions which defines the discourse. Any textual data either available on the Internet off off-line (like newspaper data, Wikipedia dump, etc) is basically connect information which cannot be treated isolated for its wholesome semantics. There is a need for an automated retrieval process with proper information extraction to structure the data for relevant and fast text analytics. The first big challenge is the conversion of unstructured textual data to structured data. Unlike other databases, graph databases handle relationships and connections elegantly. Our project aims at developing a graph-based information extraction and retrieval system.