Collaborative Filtering (CF) algorithms, used to build webbased recommender systems, are often evaluated in terms of how accurately they predict user ratings. However, current eva...
Neal Lathia, Stephen Hailes, Licia Capra, Xavier A...
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
There has been considerable work on user browsing models for search engine results, both organic and sponsored. The click-through rate (CTR) of a result is the product of the prob...
Ramakrishnan Srikant, Sugato Basu, Ni Wang, Daryl ...
Abstract. We present a framework that assesses relevance with respect to several relevance criteria, by combining the query-dependent and query-independent evidence indicating thes...
An approach to managing the architecture of large software systems is presented. Dependencies are extracted from the code by a conventional static analysis, and shown in a tabular...
Neeraj Sangal, Ev Jordan, Vineet Sinha, Daniel Jac...