Irena et al., 2024 - Google Patents
Fairness and Bias in E-commerce Recommendation Systems: A Literature ReviewIrena et al., 2024
- Document ID
- 17060981166442507640
- Author
- Irena A
- Wahyudi A
- Wairooy I
- Makalew B
- Publication year
- Publication venue
- 2024 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)
External Links
Snippet
The paper presents one of the most important themes in the fair treatment and biases of e- commerce recommendation algorithms. Algorithms recommending products to users have a dramatic impact on their shopping experience; that is, online shopping has rapidly grown in …
- 238000012552 review 0 title description 10
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
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- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/06—Buying, selling or leasing transactions
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