Centrality and Diversity in Search: Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition
暫譯: 搜尋中的中心性與多樣性：在人工智慧、機器學習、社交網絡與模式識別中的角色

Murty, M. N., Biswas, Anirban

Centrality and Diversity in Search: Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition
  • 出版商: Springer
  • 出版日期: 2019-08-24
  • 售價: $2,420
  • 貴賓價: 9.5 折 $2,299
  • 語言: 英文
  • 頁數: 94
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030247120
  • ISBN-13: 9783030247126
  • 相關分類: Machine Learning

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商品描述

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.

商品描述(中文翻譯)

中央性（centrality）和多樣性（diversity）的概念在搜尋演算法中非常重要，並在人工智慧（AI）、機器學習（ML）、社交網絡和模式識別的應用中扮演著核心角色。本書探討了中央性和多樣性在表示、回歸、排名、聚類、優化和分類中的重要性。

本書旨在讓廣泛的讀者群能夠理解。只需具備本科階段的基本數學背景，該書適合高年級本科生、研究生以及從事機器學習、資料探勘、社交網絡和模式識別的研究人員。

作者簡介

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.

作者簡介(中文翻譯)

穆爾提博士 (Dr. M.N. Murty) 是印度班加羅爾印度科學研究院計算機科學與自動化系的教授。阿尼爾班·比斯瓦斯 (Anirban Biswas) 是該機構的教學助理。

穆爾提教授的其他出版物包括施普林格 (Springer) 出版的書籍 支持向量機與感知器 (Support Vector Machines and Perceptrons)、大型數據集的壓縮方案 (Compression Schemes for Mining Large Datasets) 和 模式識別：算法方法 (Pattern Recognition: An Algorithmic Approach)。

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