M.N. Murty & Anirban Biswas 
Centrality and Diversity in Search [PDF ebook] 
Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition

Підтримка

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.

 

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Зміст

Introduction.- Searching.- Representation.- Clustering and Classification.- Ranking.- Centrality and Diversity in Social and Information Networks.- Conclusion.

Про автора

Dr. M.N. Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore, India.
Anirban Biswas is a Teaching Assistant at the same institution.

Prof. Murty’s other publications include the Springer titles Support Vector Machines and Perceptrons, Compression Schemes for Mining Large Datasets, and Pattern Recognition: An Algorithmic Approach.

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Мова Англійська ● Формат PDF ● Сторінки 94 ● ISBN 9783030247133 ● Розмір файлу 2.1 MB ● Видавець Springer International Publishing ● Місто Cham ● Країна CH ● Опубліковано 2019 ● Завантажувані 24 місяців ● Валюта EUR ● Посвідчення особи 7127721 ● Захист від копіювання Соціальний DRM

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