This book Graphs: Algorithms and Mining refers to the computational techniques used to analyse, extract insights from, and manipulate graph data structures. These techniques are essential for understanding the structure, properties, and relationships within graphs, which are prevalent in various real-world applications. Graph algorithms and mining play a crucial role in understanding the structure and dynamics of complex networks, enabling applications such as social network analysis, recommendation systems, network security, and biological network analysis. Learning a course that covers topics such as graph theory, data mining, distributed computing, text mining, and web search is crucial for several reasons, and its real -world applications are extensive. The book will help the students/readers: a To understand graphs and their applications, To understand the role of distributed computing in data intensive data mining o To study how to search graphs based on key words a To understand how text mining is different from data mining and how to mine it To understand what goes into the web search and to study methods of web search and their improvements To understand how to mine complex structures other than records while retaining the relations among the entities • To learn about analysing large datasets using scalable and practical methods.