A Novel Framework for Predicting Performance of Keyword Queries Over Database

Abstract

In fast-growing information era, business or commercial RDBMS provides huge data access in the form of distributed database, and this data can be accessed by keyword queries very easily, because no need to know structured query languages which is problem for almost end user, and they do not know SQL but needs efficient result; with the help of keyword query interface (KQI), it is possible but often has problem like low ranking quality, i.e., low precision values or recall values, as shown in recent benchmarks. Because of ambiguity in keyword-based search, query result needs improvement. Effectiveness of keyword query should be decided based on query result. It attracts more improvement because huge data creates more complication, and for efficient results, query should be appropriate. Commercial database must support efficient approach to deal with such issues like low precision value of result; by existing methods, precision value is low because of ambiguous interpretation of queries, so in this paper, we try to rank the result according to similarity score based on mathematical model to find proper ranking of result to give efficient result of keyword-based queries.