ystem (Extended Abstract) Gianna M. Del Corso1 Antonio Gull´ı1,2 Francesco Romani1 1 Dipartimento di Informatica, University of Pisa, Italy 2 IIT-CNR, Pisa
Gianna M. Del Corso, Antonio Gulli, Francesco Roma...
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
This paper presents a comparative study on two key problems existing in extractive summarization: the ranking problem and the selection problem. To this end, we presented a system...
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...