An intelligent query approach by integrating visual queries with full-text search

Abstract

This research focuses on a combined query approach for handling structured and unstructured data. A Visual Query System (VQS) is usually developed for handling structured data. It enables end users to formulate queries through visual representations without the need of having knowledge of database and query languages. As an important branch of today's information retrieval technology, Full-Text Search (FTS) is an important approach for dealing with unstructured data. Hence, a hybrid system can be developed, which integrates a Visual Query System with a Full-Text Search engine and which acts as an intelligent search interface. A customized ranking algorithm can rank the results according to their relevance. This hybrid approach converts the natural language text queries and visual queries into a database query language, such as SQL. It can be adopted for different examples of data with a combination of structured and unstructured types to provide an efficient query interface solution. In particular, it can be integrated in web search engines to integrate structured data with unstructured data in the search interface.