We present an empirically grounded method for evaluating content selection in summarization. It incorporates the idea that no single best model summary for a collection of documen...
While various models of undo have been proposed over the years, no empirical study has yet been done to discover which model of undo most closely aligns with what users expect an ...
Aaron G. Cass, Chris S. T. Fernandes, Andrew Polid...
This paper proposes a selective procedure inlining scheme to improve a multi-grain parallelism, which hierarchically exploits the coarse grain task parallelism among loops, subrou...
Jun Shirako, Kouhei Nagasawa, Kazuhisa Ishizaka, M...
WebCLEF is about supporting a user who is an expert in writing a survey article on a specific topic with a clear goal and audience by generating a ranked list with relevant snippet...
Arnold Overwijk, Dong Nguyen, Claudia Hauff, Dolf ...
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...