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Recommendation System for Answering Missing Tuples


Pekhale Kanchan Anil , MET?s Institute of Engineering, Adgoan, Nashik, Maharashtra, India; Dr. K. V. Metre, MET?s Institute of Engineering, Adgoan, Nashik, Maharashtra, India


Top-k Question, Dominating Question, Skyline Queries, ConQueR Method


In the recent years, the quality and the usability of database systems have received more attention. The performance of database systems has gained more improvement in the past decades so, they are more and more difficult to use. The why-not questions are the users need to know why her expected tuples are not shown up in the query results i.e. the features of explaining missing tuples in database queries. Database systems is having the capability that enables users to seek clarifications on expected query results as well as the absence of expected tuples (i.e. missing tuples). It would be very helpful to users if they referred why-not questions to seek clarifications on expected tuples in query results. The problem of answering why-not questions on top-k queries, there are two algorithms to answer such why-not questions efficiently. In proposed system user can give a SQL query as input. The system includes Selection, Projection, Join, Union and Aggregation (SPJUA) query operations. After execution of query user expected answer is not in query result, then user can ask a why-not question for expected result. In a Why-Not Top-K Question algorithm the weighting value is calculated for an expected result. The Weighting value is used for the highest preference of user expected tuples which limits its practicability. In a Why-Not Top-K Dominating Question algorithm there is no need to specify the weighting value. These algorithms are able to return high quality explanations efficiently. Then Refined Query is generated for user expected answer. The ConQueR method generates the refined query by modifying the predicates value which is provided by user in the query. Many users love to pose those kinds of queries when they are making multi-criteria decisions and user need approximate information from the huge Database.

Other Details

Paper ID: IJSRDV4I50547
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 921-925

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