preface

When I was nearing completion of my previous book, Graph-Powered Machine Learning, I reached out to my acquisitions editor, Mike Stephens, with a proposal for a natural continuation. That earlier work introduced knowledge graphs and demonstrated how they could be built using natural language processing, but many readers pointed out that graph neural networks were a significant missing piece. My proposed book would fill that gap while extending the knowledge graph story further, including detailed analysis and building techniques.

Mike accepted the proposal, and I embarked on a new adventure with the working title Knowledge Graphs Applied. Recognizing the scope of the challenge, I invited three colleagues from GraphAware—Fabio, Giuseppe, and Vlastimil—to join the effort, confident that their combined expertise would be invaluable. I naively thought that if one author could write a book in four years, four authors could complete a book in just a year. That assumption proved as flawed as expecting nine women to deliver a baby in one month.