Titlebook: Advances in Bias and Fairness in Information Retrieval; Third International Ludovico Boratto,Stefano Faralli,Giovanni Stilo Conference pro

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书目名称Advances in Bias and Fairness in Information Retrieval影响因子(影响力)




书目名称Advances in Bias and Fairness in Information Retrieval影响因子(影响力)学科排名




书目名称Advances in Bias and Fairness in Information Retrieval网络公开度




书目名称Advances in Bias and Fairness in Information Retrieval网络公开度学科排名




书目名称Advances in Bias and Fairness in Information Retrieval被引频次




书目名称Advances in Bias and Fairness in Information Retrieval被引频次学科排名




书目名称Advances in Bias and Fairness in Information Retrieval年度引用




书目名称Advances in Bias and Fairness in Information Retrieval年度引用学科排名




书目名称Advances in Bias and Fairness in Information Retrieval读者反馈




书目名称Advances in Bias and Fairness in Information Retrieval读者反馈学科排名

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Teen TV Translations: Across the Pond quality of the choices. By simulating users’ choices, influenced by RSs, it was shown that algorithmic biases, such as the tendency to recommend popular items, are transferred to the users’ choices..In this paper we conjecture that the effect of an RS on the quality and distribution of the users’ c

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The Professional Career of A. G. Dennistoni.e., frequently rated items) are recommended frequently while less popular items are recommended rarely or not at all. Researchers adopted two approaches to examining popularity bias: (i) from the users’ perspective, by analyzing how far a recommendation system deviates from user’s expectations in

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Intelligence and Strategy in World War IIostly promoting only already popular items. Various approaches of quantifying and mitigating such biases were put forward in the literature. Most recently, . methods were proposed that aim to match the popularity of the recommended items with popularity preferences of individual users. In this paper

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K. G. Robertson (Lecturer in Sociology)the most prominent is ., which analyzes if existing imbalances in the input data are exacerbated in the produced recommendations. On the other hand, . ensure that the recommendations reflect the distribution of the original preferences of each user (e.g., in terms of item genres). In this paper, we

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K. G. Robertson (Lecturer in Sociology)n particular, since relevance in information retrieval (IR) is a multi-dimensional concept, we study whether the value and quality of the retrieved documents for some . queries can be judged differently when the content of the documents represents different genders. To this aim, we conduct a set of