Information retrieval from digital libraries in SQL
Proceedings of the 10th ACM workshop on Web information and data management
Keyword search on structured and semi-structured data
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Fast and dynamic OLAP exploration using UDFs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Evaluating statistical tests on OLAP cubes to compare degree of disease
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
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Query suggestion is well-known to enhance the user's search for relevant documents. In this work, we propose a novel technique that emulates a human skill when searching or exploring digital collections. In general, a user begins searching by providing a naïve query and then analyzes the retrieved documents in order to refine the query search. We decided to emulate this behavior by generating alternative queries using OLAP. Such queries are the result of performing multiple data summarizations on digital libraries, and then generating cuboids depending on the correlation between the keywords of the collection and the subset of keywords belonging to the previous search. Moreover, we introduce techniques to efficiently obtain query suggestions inside the DBMS by exploiting UDFs and SQL queries.