ACCESS ENABLED DATABASE QUERY RECOMMENDATION SYSTEM (original) (raw)
Extensive exploration of the database is essential for an effective information mining process. Massive volumes of complex data from various sources or platforms that are integrated and available in datamarts have to be analyzed and studied for any form of knowledge discovery. For example, users like scientists need to query large databases for scientific data analysis and exploration. However, all users may not possess the competencies in Structured Query Language that is in general required, to query relevant data from relational database. Inexperienced users will seldom be proficient with the structural details of the schema and databases. This knowledge is required for all database related activities like generating reports for ad-hoc business requests. A database query recommendation system is a system that assists users by presenting personalized database query recommendations. The framework attempts to identify similarities with previous users\\\' information needs and recommend queries to the current user. An access enabled recommendation engine is an extension to the query recommendation system that supports the capability of recommending queries based on the user\\\'s privileges to access a particular database object. For example, the system will refrain from suggesting a query that refers to a database table with confidential data, to a user with insufficient privileges, regardless of whether the query qualifies with highest similarity for recommendation.
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