On m-impact regions and standing top-k influence problems

In this paper, we study the ��-impact region problem (mIR). In a context where users look for available products with top-�� queries, mIR identifies the part of the product space that attracts the most user attention. Specifically, mIR determines the kind of attribute values that lead a (new or exis...

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Main Authors: TANG, Bo, MOURATIDIS, Kyriakos, HAN, Mingji
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語言:English
出版: Institutional Knowledge at Singapore Management University 2021
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/6216
https://ink.library.smu.edu.sg/context/sis_research/article/7219/viewcontent/3448016.3452832.pdf
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機構: Singapore Management University
語言: English
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總結:In this paper, we study the ��-impact region problem (mIR). In a context where users look for available products with top-�� queries, mIR identifies the part of the product space that attracts the most user attention. Specifically, mIR determines the kind of attribute values that lead a (new or existing) product to the top-�� result for at least a fraction of the user population. mIR has several applications, ranging from effective marketing to product improvement. Importantly, it also leads to (exact and efficient) solutions for standing top-�� impact problems, which were previously solved heuristically only, or whose current solutions face serious scalability limitations. We experiment, among others, on data mined from actual user reviews for real products, and demonstrate the practicality and efficiency of our algorithms, both for mIR and for standing top-�� impact problems