Relational Data Clustering: Models, Algorithms, and Applications (Hardcover)

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.

《關聯數據聚類：模型、算法和應用》是作者多年來對這一主題進行廣泛研究的結晶。本書介紹了關聯數據聚類的基礎和應用，描述了理論模型和算法，並通過實例展示如何應用這些模型和算法解決實際問題。

在界定了這一領域之後，本書介紹了不同類型的關聯數據聚類模型，提出了相應的算法，並通過廣泛的實驗結果展示了這些模型和算法的應用。作者涵蓋了關聯數據聚類的六個主題：

1. 雙類型異構關聯數據的聚類
2. 多類型異構關聯數據
3. 同質關聯數據聚類
4. 最一般情況下的關聯數據聚類
5. 個體關聯聚類框架
6. 關於演化聚類的最新研究

本書注重關聯數據聚類的實際算法推導和理論框架構建，為該領域的進展提供了完整、自包含的介紹。