An Efficient Forecasting of Difficult Keyword Queries over Database
Keyword queries on information bases offer easy accessibility to data, however usually suffer from low ranking quality, i.e., low exactitude and/or recall, as shown in recent benchmarks. It'd be helpful to spot queries that square measure probably to own low ranking quality to improve the user satisfaction. For example, the system could recommend to the user different queries for such onerous queries. The authors set forth a high-principled framework and proposed novel algorithms to live the degree of the issue of a question over a dB, exploitation the ranking strength principle. Supported their framework, they tend to propose novel algorithms that with efficiency predict the effectiveness of a keyword question.