Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
ct 8 In this paper, a new robust relevance model is proposed that can be applied to both pseudo and true relevance feedback 9 in the language-modeling framework for document retrie...
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Pa...
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...