The book "Invariant-parametric representation and generalized associative processing of symbolic and semantic information" edited by G. P. Tokmakov is a unique study that immerses the reader in the world of complex concepts related to information processing. This work, carried out by a team of authors, offers a fresh look at the methods and approaches used in the field of computer science and information theory, which makes it especially relevant for specialists and students interested in modern technologies and their application. The book examines the key aspects of the invariant-parametric representation, which allows you to effectively process both symbolic and semantic information. The authors aim to show how these techniques can be applied in a variety of fields, from artificial intelligence to natural language processing. They emphasize the importance of associative information processing, which allows for more flexible and adaptive systems capable of learning and self-development. This book will be of particular interest to students, graduate students, and researchers in computer science, mathematics, and artificial intelligence. It can also attract the attention of practitioners working in the field of software development, data processing systems and machine learning technologies. If you are looking for a deep and meaningful study that will help you better understand modern approaches to information processing, then this work will be a real find for you. The topics raised in the book cover a wide range of issues, including the theoretical foundations of information processing, methods of data analysis, and algorithms used to create intelligent systems. The authors pay special attention to the practical aspects of the application of their developments, which makes the material accessible to those who do not have deep knowledge in this field. The book emphasizes the importance of an interdisciplinary approach that integrates different fields of science and technology, making it particularly valuable for researchers seeking to integrate knowledge. The style of presentation of the authors is clear and logical, which allows the reader to easily assimilate complex concepts. Each chapter of the book is structured in such a way as to gradually introduce the reader to the topic, starting with the basic concepts and ending with more complex and in-depth aspects. This makes the book not only a scientific work, but also a teaching aid that can be used in educational institutions. G. P. Tokmakov and his colleagues are known for their work in information theory and data processing. Their previous publications have also been popular with researchers and practitioners. In this book, they continue to develop their ideas, offering new solutions to the pressing problems faced by specialists in their field. If you are looking for books on the topic of information processing, pay attention to such works as “Information Processing and Management” and “Artificial Intelligence: Modern Approaches” These books can complement your knowledge and deepen your understanding of the topics addressed in Invariant Parametric Representation and Generalized Associative Processing of Symbolic and Meaningful Information. In conclusion, this work represents an important contribution to the field of computer science and data processing. It not only expands the horizons of existing knowledge, but also offers practical solutions for solving complex problems. Readers interested in modern methods of information processing will find in this book many useful ideas and inspirations for further research.