Efficient Top-k Keyword Search in Relational Databases Considering Maximum Integrated Candidate Network (MICN)

In the era of Big Data, exploring vast amount of information without requiring to have knowledge of the query language and the underlying structure of data is very essential. Keyword search over RDBMSs (Relational Database Management Systems) has been an interesting method for this issue during the past decade. Although, many approaches have been proposed in this hot research topic, they still suffer from low effectiveness in retrieving top-k most related answers on real datasets. In this paper, an approach is proposed that can construct a Maximum Integrated Candidate Network (MICN) to avoid all the repetitive operations in order to answer most of queries efficiently. MICN can be build up with the minimal database access which causes effective response time. Based on comprehensive empirical studies using multiple real-world databases including ISC citation center data in practical mode, the proposed approach significantly improves the efficiency of answering queries.