Abstract
Ranking is an important task in machine learning, information retrieval, and data mining. We consider different notions like similarity and density and their role in ranking. Further, we discuss how centrality and diversity are captured in a variety of ranking tasks.
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© 2019 The Author(s), under exclusive license to Springer Nature Switzerland AG
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Murty, M.N., Biswas, A. (2019). Ranking. In: Centrality and Diversity in Search. SpringerBriefs in Intelligent Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-24713-3_5
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DOI: https://doi.org/10.1007/978-3-030-24713-3_5
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-030-24713-3
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