دانلود کتاب پردازش زبان طبیعی و کاربردها

Natural language processing is a discipline that integrates linguistics, computer science, and mathematics, studying various theories and methods for effective communication between humans and computers using natural language. The goal of natural language processing is to enable machines to understand language as intelligently as humans do, with the ultimate goal of narrowing the gap between human communication (natural language) and computer understanding (machine language). Natural language processing is hailed as the “jewel in the crown of artificial intelligence.” Microsoft’s global vice president and renowned artificial intelligence expert Shen Xiangyang clearly stated at the China Computer Conference: “He who masters language masters the world.” Natural language processing has become a difficult and hot spot in artificial intelligence research, harboring opportunities to change the future of the world. A report by Mordor Intelligence shows that the global natural language processing market was $10.72 billion in 2020, and is expected to grow to $48.46 billion by 2026, with a compound annual growth rate of 26.84%. With the global spread of the COVID-19 pandemic, the growth of natural language processing in the field of healthcare has been particularly rapid. In recent years, there have been many excellent monographs or textbooks in the field of natural language processing, but most of them mainly introduce classic algorithms and related technologies of natural language processing, and there are not many that combine actual systems and application practices. I started offering the elective course “Big Data Analysis and Application” at Beijing Institute of Technology in 2016, and started offering the compulsory course “Big Data Processing Technology” for third-year students majoring in artificial intelligence at Beijing Institute of Technology in 2022, trying to combine natural language processing with big data and artificial intelligence. Using a research-based teaching method, I give classic task propositions of natural language processing, and students are required to give a review report in groups, detailing the classic algorithms of each technical point of natural language processing, reflecting the frontier progress of international academic research in the past 3 years, and finally giving an intuitive demonstration system and conducting experimental verification. The final exam of the course requires team cooperation to complete a natural language processing project with a certain degree of innovation, which is independently reviewed by experts from industry, academia, and research outside the school. After 6 years of continuous exploration, the course has received wide acclaim from more than 1000 students who have taken the course, with an average final score of 94.73. With the continuous improvement of the teaching practice system, I hope to share the results of more than 20 years of research in natural language processing and 6 years of teaching practice, and finally complete this textbook closely combined with natural language processing and application. This book is divided into five parts: The Part I mainly includes an overview of natural language processing and its applications, classic deep learning platforms and algorithms, the latest developments in deep learning, and pre-trained language models; The Part II mainly includes web crawler technology, multi-format document parsing and management, speech-to-text recognition, image semantic representation and character recognition, Chinese word segmentation, and part-of-speech tagging; The Part III includes sentiment analysis, new word discovery, named entity recognition and keyword extraction, automatic construction, application of big data knowledge graphs, etc.; The Part IV includes information filtering, text classification, text clustering, text proofreading, automatic summarization; The Part V mainly introduces some distinctive natural language processing application projects and cases. The feature of this book is that it integrates academic frontiers, practical applications, and teaching achievements, fully reflecting the international academic frontier progress in the direction of big data, artificial intelligence, and natural language processing, and incorporating the innovative achievements of the author team in the direction of natural language processing and applications for more than 20 years. The related achievements have successively won the first and second prizes of the Science and Technology Progress Award of the Xinjiang Uygur Autonomous Region, and the first prize of the Qian Weichang Chinese Information Processing Science and Technology Award. This book has absorbed the teaching achievements of “Big Data Analysis and Application” and “Big Data Processing Technology” for more than 6 years, and included several excellent projects of research groups as application cases. As a supporting website and download base for the achievements of this book, the NLPIR (Natural Language Processing and Information Retrieval) sharing platform provides demonstrations of actual results and downloads of various resources. This book can be used as a textbook for graduate students and senior undergraduates in the direction of natural language processing, and can also be used as a reference for researchers, engineering technicians, and enthusiasts in the direction of natural language processing.