Natural Language Query Processing for Relational Database using EFFCN Algorithm
Keywords:
Natural Language Query, Structured Query, Precision, Recall, F1-measureAbstract
This paper addresses the procedure to develope an interface to natural language database that is efficient and flexible to handle unrestricted natural language and interpret the request appropriately called as EFFCN, stands for EFFiciently Compliant Natural language interface to database. The Experimental set up is created by developing a database named as CPVBase. The database holds the tables instituted with the sample records of Customer, Product, Vendor and Invoice data. The database tables have foreign key references to the other tables epitomizing a relation database management system. This paper explains about various technical segments of the implementation of the EFFCN algorithm. The working procedure of the algorithm for the natural language statement transformation into SQL query is depicted. The EFFCN algorithm's precision and recall measures for the score of relevancy is obtained with the success rate of 84%. The PR curve shows the variation of precision and recall measures tested on discrete set of input queries.
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