Learning to rank for information retrieval

Tyliu

Sujets

• Informatique
• Marketing et communication

Informations

• Publié par: oeufdepaques
• Nombre de lectures: 298
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

Learning to Rank for Information Retrieval Tie-Yan Liu Lead Researcher Microsoft Research Asia 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 1The Speaker • Tie-Yan Liu – Lead Researcher, Microsoft Research Asia. – Ph.D., Tsinghua University, China. – Research Interests: Learning to Rank, Large-scale Graph Learning. – ~70 Papers: SIGIR(9), WWW(3), ICML (3), KDD(2), etc. – Winner of Most Cited Paper Award, JVCIR, 2004 - 2006. – Senior PC Member of SIGIR 2008. – Co-chair, SIGIR Workshop on Learning to Rank, 2008. – Co-chair, SIGIR Workshop on Learning to Rank, 2007. – Speaker, Tutorial on Learning to Rank, SIGIR 2008 (to be given in July), AIRS 2008, etc. 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 2This Tutorial • Learning to rank for information retrieval – But not other generic ranking problems. • Supervised learning – But not unsupervised or semi-supervised learning. – Mostly discriminative learning but not generative learning. • Learning in vector space – But not on graphs or other structured data. • Mainly based on papers published at SIGIR, WWW, ICML, KDD, and NIPS in the past five years. – Papers at other conferences and journals might not be covered comprehensively in this tutorial. 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 3Background Knowledge Required • Information Retrieval – We will just briefly introduce, but not comprehensively review the literature of IR. • Machine Learning – We will assume you are familiar with regression, classification and their learning algorithms, such as SVM, Boosting, NN, etc. – No comprehensive introduction to these algorithms and their principles will be given. • Probability Theory. • Linear Algebra. • Optimization. 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 4Outline • Ranking in Information Retrieval • Learning to Rank – Overview – Pointwise approach – Pairwise approach – Listwise approach • Summary 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 5Ranking in Information Retrieval 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 6We are Overwhelmed by Flood of Information 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 7Information Explosion 2008? 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 84/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 9Search Engine as A Tool 4/20/2008 Tie-Yan Liu @ Tutorial at WWW 2008 10