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 :
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