• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

OLAP4R: A Top-K Recommendation System for OLAP Sessions

Vol. 11, No.6, June 30, 2017
10.3837/tiis.2017.06.009, Download Paper (Free):

Abstract

The Top-K query is currently played a key role in a wide range of road network, decision making and quantitative financial research. In this paper, a Top-K recommendation algorithm is proposed to solve the cold-start problem and a tag generating method is put forward to enhance the semantic understanding of the OLAP session. In addition, a recommendation system for OLAP sessions called “OLAP4R” is designed using collaborative filtering technique aiming at guiding the user to find the ultimate goals by interactive queries. OLAP4R utilizes a mixed system architecture consisting of multiple functional modules, which have a high extension capability to support additional functions. This system structure allows the user to configure multi-dimensional hierarchies and desirable measures to analyze the specific requirement and gives recommendations with forthright responses. Experimental results show that our method has raised 20% recall of the recommendations comparing the traditional collaborative filtering and a visualization tag of the recommended sessions will be provided with modified changes for the user to understand.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Youwei Yuan, Weixin Chen, Guangjie Han and Gangyong Jia, "OLAP4R: A Top-K Recommendation System for OLAP Sessions," KSII Transactions on Internet and Information Systems, vol. 11, no. 6, pp. 2963-2978, 2017. DOI: 10.3837/tiis.2017.06.009

[ACM Style]
Yuan, Y., Chen, W., Han, G., and Jia, G. 2017. OLAP4R: A Top-K Recommendation System for OLAP Sessions. KSII Transactions on Internet and Information Systems, 11, 6, (2017), 2963-2978. DOI: 10.3837/tiis.2017.06.009