Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing.
Matching, which is to measure the relevance of a document to a query or interest of a user to an item, is a key problem in both search and recommendation. Machine learning has been exploited to...
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With the rapid progress of deep neural models and the explosion of data resources, dialogue systems that supports extensive topics and chit-chat conversations are emerging in natural language...