Connecting the dots between news articles

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Determinantal Point Processes for Machine Learning (2012, methodology): “Shahaf and Guestrin [128], for example, assume that the thread endpoints are specified, and Chieu and Lee [27] require a set of query words.”
Story-Driven Summarization for Egocentric Video (2013, methodology): “In the following, our definitions for influence and coherency are directly adapted from [24], where we draw an analogy between the news articles and words in that work, and the subshots and visual objects in our work.”
Learning causality for news events prediction (2012, background): “Shahaf and Guestrin [35] essentially detect a whole causality chain – given two news articles, they provide a coherent small number of news items connecting them.”
Learning to model relatedness for news recommendation (2011, background): “A recent work [32] focused on connecting two news stories in two different time points through finding a set of coherent stories in the middle.”