• Anumala Reethika Reddy
• G. Sharmila Sujatha

keyword queries on databases provide easy access to data, but often suffer from low ranking quality, i.e., low precision and/or recall, as shown in recent benchmarks. It would be useful to identify queries that are likely to have low ranking quality to improve the user satisfaction. For instance, the system may suggest to the user alternative queries for such hard queries. In this paper, we analyze the characteristics of hard queries and propose a novel framework to measure the degree of difficulty for a key-word query over a database, considering both the structure and the content of the database and the query results. We evaluate our query difficulty prediction model against two effectiveness benchmarks for popular keyword search ranking methods. Our empirical results show that our model predicts the hard queries with high accuracy. Further, we present a suite of optimizations to minimize the incurred time overhead

"Study on Efficient Prediction of Difficult Keyword Queries Over Databases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.742-746, June 2019, Available :http://www.jetir.org/papers/JETIR1907412.pdf

"Study on Efficient Prediction of Difficult Keyword Queries Over Databases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp742-746, June 2019, Available at : http://www.jetir.org/papers/JETIR1907412.pdf