Query Morphing: A Proximity-Based Data Exploration for Query Reformulation

With the increase of information technology, multiple terabytes of structured and unstructured data are generated on daily basis through various sources, such as sensors, lab simulations, social media, web blogs, etc. Due to big data occurrences, acquisition of relevant information is getting complex processing task. These data are often stored and kept in the vast schema, and thus formulating data retrieval requires a fundamental understanding of the schema and content. A discovery-oriented search mechanism delivers good results here, as the user can stepwise explore the database and stop when the result content and quality meet. In this, a naive user often transforms data request in order to discover relevant items; morphing is a historical approach for the generation of various transformations of input. We proposed “Query Morphing”, an approach for query reformulation based on data exploration. Various design issues and implementation constraints of the proposed approach are also listed.