Enhancing Keyword Query Results Over Database for Improving User Satisfaction

Abstract

Storing data in relational databases is widely increasing to support keyword queries but search results does not gives effective answers to keyword query and hence it is inflexible from user perspective. It would be helpful to recognize such type of queries which gives results with low ranking. Here we estimate prediction of query performance to find out effectiveness of a search performed in response to query and features of such hard queries is studied by taking into account contents of the database and result list. One relevant problem of database is the presence of missing data and it can be handled by imputation. Here an inTeractive Retrieving-Inferring data imputation method (TRIP) is used which achieves retrieving and inferring alternately to fill the missing attribute values in the database. So by considering both the prediction of hard queries and imputation over the database, we can get better keyword search results.