We describe a new approach to information retrieval: algorithmic mediation for intentional, synchronous collaborative exploratory search. Using our system, two or more users with a common information need search together, simultaneously. The collaborative system provides tools, user interfaces and, most importantly, algorithmically-mediated retrieval to focus, enhance and augment the team's search and communication activities. Collaborative search outperformed post hoc merging of similarly instrumented single user runs. Algorithmic mediation improved both collaborative search (allowing a team of searchers to find relevant information more efficiently and effectively), and exploratory search (allowing the searchers to find relevant information that cannot be found while working individually).

Temporal aspects of documents can impact relevance for certain kinds of queries. In this paper, we build on earlier work of modeling temporal information. We propose an extension to the Query Likelihood Model that incorporates query-specific information to estimate rate parameters, and we introduce a temporal factor into language model smoothing and query expansion using pseudo-relevance feedback. We evaluate these extensions using a Twitter corpus and two newspaper article collections. Results suggest that, compared to prior approaches, our models are more effective at capturing the temporal variability of relevance associated with some topics.

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Hitchcock is a system that allows users to easily create custom videos from raw video shot with a standard video camera. In contrast to other video editing systems, Hitchcock uses automatic analysis to determine the suitability of portions of the raw video. Unsuitable video typically has fast or erratic camera motion. Hitchcock first analyzes video to identify the type and amount of camera motion: fast pan, slow zoom, etc. Based on this analysis, a numerical "unsuitability" score is computed for each frame of the video. Combined with standard editing rules, this score is used to identify clips for inclusion in the final video and to select their start and end points. To create a custom video, the user drags keyframes corresponding to the desired clips into a storyboard. Users can lengthen or shorten the clip without specifying the start and end frames explicitly. Clip lengths are balanced automatically using a spring-based algorithm.