Relational Data Clustering: Models, Algorithms, and Applications (Hardcover)
暫譯: 關聯資料聚類:模型、演算法與應用(精裝版)

Bo Long, Zhongfei Zhang, Philip S. Yu

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商品描述

A culmination of the authors’ years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational data clustering. It describes theoretic models and algorithms and, through examples, shows how to apply these models and algorithms to solve real-world problems.

 

After defining the field, the book introduces different types of model formulations for relational data clustering, presents various algorithms for the corresponding models, and demonstrates applications of the models and algorithms through extensive experimental results. The authors cover six topics of relational data clustering:

 

 

  1. Clustering on bi-type heterogeneous relational data
  2. Multi-type heterogeneous relational data
  3. Homogeneous relational data clustering
  4. Clustering on the most general case of relational data
  5. Individual relational clustering framework
  6. Recent research on evolutionary clustering

 

This book focuses on both practical algorithm derivation and theoretical framework construction for relational data clustering. It provides a complete, self-contained introduction to advances in the field.

商品描述(中文翻譯)

這本書是作者多年深入研究該主題的結晶,名為關聯數據聚類:模型、演算法與應用,探討了關聯數據聚類的基本原理和應用。書中描述了理論模型和演算法,並通過範例展示如何將這些模型和演算法應用於解決現實世界中的問題。

在定義該領域後,書中介紹了關聯數據聚類的不同模型表述類型,呈現了對應模型的各種演算法,並通過大量實驗結果展示模型和演算法的應用。作者涵蓋了六個關聯數據聚類的主題:

1. 在雙類型異質關聯數據上的聚類
2. 多類型異質關聯數據
3. 同質關聯數據聚類
4. 在關聯數據最一般情況下的聚類
5. 個別關聯聚類框架
6. 最近的演化聚類研究

本書專注於關聯數據聚類的實用演算法推導和理論框架建構,提供了該領域進展的完整、自足的介紹。