Thesis and Dissertation Workshop (WTDBD)
Query Recommendation, SQL, Databases, Query Logs, Clustering
Database systems are becoming increasingly popular in the scientific community to support data exploration. In this scenario, users may not have the necessary knowledge about the domain of the database or how to formulate SQL queries to analyze the data. To solve this problem, we developed a study on the most recent techniques for query recommendation to improve them in such a manner that the user can receive better recommendations. In this proposal we discuss the main challenges of query recommendation systems and how clustering users can improve recommendations. Preliminary experimental results using real user query logs show that our study can generate effective query recommendations.
Márcio de Carvalho Saraiva, Carlos Eduardo Pires, Leandro Balby Marinho