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Margaris et al., 2017 - Google Patents

Improving collaborative filtering's rating prediction quality by considering shifts in rating practices

Margaris et al., 2017

Document ID
11378711608715540158
Author
Margaris D
Vassilakis C
Publication year
Publication venue
2017 IEEE 19th Conference on Business Informatics (CBI)

External Links

Snippet

Users that populate ratings databases, such as IMDB, follow different marking practices, in the sense that some are stricter, while others are more lenient. This aspect has been captured by the most widely used similarity metrics in collaborative filtering, namely the …
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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
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    • G06Q30/00—Commerce, e.g. shopping or e-commerce
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