Learning to Rank for Information Retrieval

Аннотация

This book is written for researchers and graduate students in information retrieval and machine learning. Familiarity of machine learning, probability theory, linear algebra, and optimization would be helpful though not essential as the book includes a self-contained brief introduction to the related knowledge in Chaps. 21 and 22. Because learning to rank is still a fast growing research area, it is impossible to provide a complete list of references. Instead, the aim has been to give references that are representative and hopefully provide entry points into the short but rich literature of learning to rank.