M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 12, December 2015
Matrix Factorization Based Query Recommendation
Visak Paul | Sreena Sreedhar 
Abstract: Database exploration is always a tedious task for the people who lacks skill in writing complex SQL queries. In order to aid such people, SQL recommendations are provided with the help of an interactive query recommendation system. The recommendations will be based on the current query, queries previously submitted by the user and the queries submitted by other users to the system. Based on this, the recommendation engine recommends the recommendation query to the user. The user can use this query as a template to formulate the query he wanted or he can submit the same. The recommended query will be like the query the user may want to write. The recommendation users the general concept of collaborative filtering method in which the recommendations will be based on the relationships between the queries submitted and the interests of the user. The use matrix factorization further improves the recommendation accuracy and thereby a better result for the user.
Keywords: recommender systems, matrix factorization, query recommendation, collaborative filtering
Edition: Volume 4 Issue 12, December 2015,
Pages: 169 - 173
How to Cite this Article?
Visak Paul, Sreena Sreedhar, "Matrix Factorization Based Query Recommendation", International Journal of Science and Research (IJSR), Volume 4 Issue 12, December 2015, pp. 169-173, https://www.ijsr.net/get_abstract.php?paper_id=NOV151879
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