User preference space partition and product filtering for reverse Top-k queries

  • 楊 宗樺

Student thesis: Master's Thesis


Top-k queries have been studied mainly from the perspective of the user Many researchers have focused on improving the efficiency of top-k problems However few studies have focused on the essential factors required for manufacturers to assess the potential market A novel query type namely the reverse top-k is used to assess the potential market and help manufacturers calculate the impact of their products Given a potential product reverse top-k will find the user preferences for which this product is in the top-k query result set Although several algorithms can solve the reverse top-k problem none that are available can solve the reverse top-k problem when the number of products or users is large In this paper we formally define our algorithm as FSP (filtering and space partition) and explain how FSP solves the reverse top-k problem The main idea of FSP is to use the partition of the candidate space to reduce the searching of space for products In our experimental results FSP can find the same results as other algorithms but FSP reduces the time cost from 231 msec to 32 msec
Date of Award2014 Aug 26
Original languageEnglish
SupervisorHung-Yu Kao (Supervisor)

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