Bøger af Tie-Yan Liu

This book constitutes the thoroughly refereed conference proceedings of the 10th International Conference on Web and Internet Economics, WINE 2014, held in Beijing, China, in December 2014. The 32 regular and 13 short papers were carefully reviewed and selected from 107 submissions and cover results on incentives and computation in theoretical computer science, artificial intelligence, and microeconomics.

The author of this book first reviews the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms. Scientific theoretical soundness is combined with broad development and application experiences.

Provides an introduction to the field of learning to rank, a hot research topic in information retrieval and machine learning. Learning to Rank for Information Retrieval is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners.