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

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書目名稱Advances in Bias and Fairness in Information Retrieval影響因子(影響力)




書目名稱Advances in Bias and Fairness in Information Retrieval影響因子(影響力)學科排名




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書目名稱Advances in Bias and Fairness in Information Retrieval網(wǎng)絡公開度學科排名




書目名稱Advances in Bias and Fairness in Information Retrieval被引頻次




書目名稱Advances in Bias and Fairness in Information Retrieval被引頻次學科排名




書目名稱Advances in Bias and Fairness in Information Retrieval年度引用




書目名稱Advances in Bias and Fairness in Information Retrieval年度引用學科排名




書目名稱Advances in Bias and Fairness in Information Retrieval讀者反饋




書目名稱Advances in Bias and Fairness in Information Retrieval讀者反饋學科排名

obeisance

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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舞蹈編排

Thrombolysis

革新

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

退出可食用

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

熱心

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

救護車

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