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Holland et al., 2004 - Google Patents

User preference mining techniques for personalized applications

Holland et al., 2004

Document ID
17279978014915169882
Author
Holland S
Kießling W
Publication year
Publication venue
Wirtschaftsinformatik

External Links

Snippet

Advanced personalized e-applications require comprehensive knowledge about their users' likes and dislikes in order to provide individual product recommendations, personal customer advice, and custom-tailored product offers. In our approach we model such …
Continue reading at link.springer.com (other versions)

Classifications

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    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • G—PHYSICS
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    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202—Market predictions or demand forecasting
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    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
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    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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