In this paper, we study bias in knowledge graph embeddings. We focus on gender bias in occupations, but our approach is applicable to other types of bias. We start by proposing measures for identifying bias in the dataset (i.e., in the KG) and then ...
Recommender systems are routinely equipped with standardized taxonomy that associates each item with one or more categories or genres. Although such information does not directly imply the quality of an item, the distribution of ratings vary greatly ...
Nowadays, Machine Learning (ML) systems are widely used in various businesses and are increasingly being adopted to make decisions that can significantly impact people’s lives. However, these decision-making systems rely on data-driven learning, which ...
Association for Computing Machinery
New York, NY, United States
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