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

Evolution of Extremely large databases is a vital challenge for data processing via traditional database systems, such as scientific DB, Genome DB, Social Media DB etc. As these DBs are often stored in a complex schema, and inherent vastness raises challenges to a naive user on initial data request formulation and comprehending the resulting content. A discovery-oriented search mechanism delivers good results in these information seeking scenario, as the user can stepwise explore the database and stop when the result content and quality reaches his satisfaction point. In this, understanding user’s actual search intentions and how the search motives change with session progress will help greatly in achieving a search goal. A proximity-based data exploration approach, which explores the neighborhood and subsequently guides a user to overcome these limitations, named as ‘Query morphing’ is proposed in this paper. Various design issues and implementation constraints of the proposed approach are also listed.