User preference space partition and product filters for reverse top-k queries

Zong Hua Yang, Hung-Yu Kao

研究成果: Conference contribution

摘要

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.

原文English
主出版物標題DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics
編輯George Karypis, Longbing Cao, Wei Wang, Irwin King
發行者Institute of Electrical and Electronics Engineers Inc.
頁面498-504
頁數7
ISBN(電子)9781479969913
DOIs
出版狀態Published - 2014 3月 10
事件2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014 - Shanghai, China
持續時間: 2014 10月 302014 11月 1

出版系列

名字DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics

Other

Other2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014
國家/地區China
城市Shanghai
期間14-10-3014-11-01

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 資訊系統
  • 資訊系統與管理

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