Novel Approach for Predicting Difficult Keyword Queries over Databases using Effective Ranking

Keyword queries on databases provide easy access to data, but frequently put up with the low ranking quality, i.e., low precision and recollect as shown in recent benchmarks. It would be useful to classify queries that are likely to have low ranking quality to improve the user satisfaction. For instance, the system may propose to the user alternative queries for such hard queries. In the existing work, analyses the characteristics of hard queries and propose a novel framework to measure the degree of difficulty for a keyword query in excess of a database, considering both the structure and the content of the database and the query results. However, in this system numbers of issues are there to address. They are time complexity is higher than the other system and reliability rate of the system is lowest. In order to overcome these drawbacks, we are proposing the improved ranking algorithm which is used to enhance the accuracy rate of the system. Our solution is principled, comprehensive, and efficient. This proposed system is well enhancing the reliability rate of the difficult query prediction system. From the experimentation result, we are obtaining the proposed system is well effective than the existing system in terms of accuracy rate, quality of result. Keywords— Query performance, query effectiveness, keyword query, robustness, and databases