Full Citation

Title: Efficient Influence Related Queries

Citation Type: Dissertation/Thesis

Publication Year: 2017

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Abstract: Recently, there is a surge of interest on mining valuable information from the given datasets. As one of the most important information mining tasks, influence analysis has drawn tremendous attention in both industry and academic communities. Due to the large scale of dataset, there is an emerging call for efficient processing influence related queries. In this thesis, we study three important influence related problems regarding three types of data, i.e., product and user preference data, spatio-textual objects, and set-valued data. Firstly, for product and user preference data, we formulate the problem of influence-based cost optimization on user preference functions, which is critical to unlock the great scientific and social-economic value of these data. By utilizing the classical k-level computation techniques, we show the solution space of our problem can be reduced to a finite number of possible positions (points). To efficient . . .

Url: http://unsworks.unsw.edu.au/fapi/datastream/unsworks:46145/SOURCE02?view=true

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Authors: Yang, Jianye

Institution: UNSW Australia

Department: Computer Science and Engineering

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Degree: PhD

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Data Collections: IPUMS USA

Topics: Methodology and Data Collection, Other

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