Query Recommendations: A Collaborative Fragment Based Ap-Proach Using User Based Similarities

Provided by: International Journal of Advanced Research in Computer Science & Technology (IJARCST)
Topic: Data Management
Format: PDF
Relational database systems are becoming increasingly popular in the scientific community to support the interactive exploration of large volumes of data. Handling large and voluminous data is a tough task even for experts in SQL. The problem is even more difficult for a user who lacks SQL expertise or familiarity with the database schema. This paper aims at helping this class of users by giving them suggestions of SQL queries that they might use. These SQL suggestions are selected by profiling the users past behavior and comparing them with other users.

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