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2018 | OriginalPaper | Chapter

iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention

Authors : Zhihui Yang, Jiyang Gong, Chaoying Liu, Yinan Jing, Zhenying He, Kai Zhang, X. Sean Wang

Published in: Database Systems for Advanced Applications

Publisher: Springer International Publishing

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Abstract

Exploratory data analysis over large datasets has become an increasingly prevalent use case. However, users are easily overwhelmed by the data and might take a long time to find interesting facts. In this paper, we design a system called iExplore to assist users in doing this time-consuming data exploration task through predicting user intention. Moreover, we propose an intention model to help the iExplore system have a comprehensive understanding of user’s intention. Thus, the exploratory process can be accelerated by the intention-driven recommendation and prefetching mechanisms. Extensive experiments demonstrate that the intention-driven iExplore system can significantly lighten the burden of users and facilitate the exploratory process.

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Title: iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention
Authors: Zhihui Yang
Jiyang Gong
Chaoying Liu
Yinan Jing
Zhenying He
Kai Zhang
X. Sean Wang
Publisher: Springer International Publishing
Book: Database Systems for Advanced Applications
Print ISBN: 978-3-319-91457-2

Electronic ISBN: 978-3-319-91458-9

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-91458-9_9

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