English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51572066      Online Users : 723
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/75863


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/75863


    Title: Finding k most favorite products based on reverse top-t queries
    Authors: Koh, J.-L.;Lin, C.-Y.;Chen, Arbee L.P.
    陳良弼
    Contributors: 資科系
    Keywords: Computational complexity;Query processing;Approximate solution;Greedy algorithms;Maximum coverage;Memory utilization;Multiple components;Potential customers;Quality guaranteed;Reverse top-t query;Sales
    Date: 2014-08
    Issue Date: 2015-06-16 17:34:26 (UTC+8)
    Abstract: A reverse top-t query for a product returns a set of customers, named potential customers, who regard the product as one of their top-t favorites. Given a set of customers with different preferences on the features of the products, we want to select at most k products from a pool of candidate products such that their total number of potential customers is maximized. Two versions of the problem are defined according to whether the competitive existing products are given. For solving this NP-hard problem, we first propose an incremental greedy approach to find an approximate solution of the problem with quality guaranteed. For further speeding up this basic greedy approach, we exploit several properties of the top-t queries and skyline queries to reduce the solution space of the problem. In addition, an upper bound of the potential customers is estimated to reduce the cost of computing the reverse top-t queries for the candidate products. Finally, when the candidate products are formed from multiple component tables, we propose a strategy to reduce the number of the accessed tuples in the component tables such that only the tuples that are possibly components of the top-t favorites of the customers need to be accessed. By applying these pruning strategies, we propose another faster greedy approach. The experiment results demonstrate that the proposed pruning strategies work very well and make the faster greedy algorithms for both versions of the problem achieve excellent performance on both efficiency and memory utilization. © 2013 Springer-Verlag Berlin Heidelberg.
    Relation: VLDB Journal, 23(4), 541-564
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1007/s00778-013-0336-8
    DOI: 10.1007/s00778-013-0336-8
    Appears in Collections:[資訊科學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    541-564.pdf2398KbAdobe PDF2739View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback