28 citations · 31 across the 5 of their papers we have counts for
5 papers
How UMass-FSD Inadvertently Leverages Temporal Bias
Dominik Wurzer, Yumeng Qin
First Story Detection describes the task of identifying new events in a stream of documents. The UMass-FSD system is known for its strong performance in First Story Detection compe…
Parameterizing Kterm Hashing
Dominik Wurzer, Yumeng Qin
Kterm Hashing provides an innovative approach to novelty detection on massive data streams. Previous research focused on maximizing the efficiency of Kterm Hashing and succeeded in…
Spotting Information biases in Chinese and Western Media
Dominik Wurzer, Yumeng Qin
Newswire and Social Media are the major sources of information in our time. While the topical demographic of Western Media was subjects of studies in the past, less is known about…
Spotting Rumors via Novelty Detection
Yumeng Qin, Dominik Wurzer, Victor Lavrenko +1
Rumour detection is hard because the most accurate systems operate retrospectively, only recognizing rumours once they have collected repeated signals. By then the rumours might ha…
Randomised Relevance Model
Dominik Wurzer, Miles Osborne, Victor Lavrenko
Relevance Models are well-known retrieval models and capable of producing competitive results. However, because they use query expansion they can be very slow. We address this slow…