DocumentCode
3592107
Title
Recommending Next Query in an OLAP Session
Author
Singh, Amit ; Parimala, N.
Author_Institution
Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India
fYear
2014
Firstpage
73
Lastpage
80
Abstract
Invariably, users formulate a sequence of OLAP queries, referred to as a session, in order to arrive at the intended analysis of the data in a data warehouse. Formulating this sequence is considered a formidable task. OLAP query recommendation addresses the formulation of the next query in an ongoing session. In this paper, to recommend the next query to the user, we apply the collaborative filtering strategy which takes into account the former queries issued by all the users. Our framework relies on similarity between query sessions and recommends a query from the closest session based on its proximity to the last query in the current session. A set of experiments show the effectiveness of our approach.
Keywords
collaborative filtering; data mining; query formulation; query processing; recommender systems; OLAP queries; OLAP query recommendation; OLAP query sequence formulation; OLAP session; collaborative filtering strategy; data warehouse; next query recommendation; Collaboration; Current measurement; Data warehouses; Navigation; Q measurement; Weight measurement; MDX; OLAP; Query Recommendation; Query Session;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Business Intelligence (ISCBI), 2014 2nd International Symposium on
Print_ISBN
978-1-4799-7551-8
Type
conf
DOI
10.1109/ISCBI.2014.23
Filename
7119537
Link To Document