Centrality and Diversity in Search
Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition
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Beschreibung
The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification.
The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition.
Presents a detailed examination of the role of centrality and diversity in search Discusses tasks in machine learning, data mining, pattern recognition, and information retrieval Describes applications in social and information networks
Autor*in
M.N. Murty
Themen in »Centrality and Diversity in Search«
Centrality Diversity Search Artificial Intelligence Deep Learning Machine Learning Pattern Recognition Social Networks Optimization Representation