University of Glasgow at TREC 2014: Experiments with Terrier in Contextual Suggestion, Temporal Summarisation and Web Tracks
GLASGOW UNIV (UNITED KINGDOM)
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In TREC 2014, we focus on tackling the challenges posed by the Contextual Suggestion and Temporal Summarisation tracks, as well as enhancing our existing technologies to tackle risk-sensitivity as part of the Web track, building upon our Terrier Information Retrieval Platform. In particular for the Contextual Suggestion track, we propose a novel bundled venue retrieval approach and experiment with text-based summarisation for building the venue description. For our participation to the Temporal Summarisation track we propose a general framework for performing summarisation over time and two new real-time filtering approaches that leverage the semi-structured nature of news articles to enhance summary coverage. For the TREC Web track, we investigated a novel risk-sensitive learning to rank approach that is based on hypothesis testing and examined approaches that selectively apply different retrieval techniques based upon the query, with the aim of minimising risk.
- Information Science