Chancellery Research - Research Publications

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    2 Document Compaction for Efficient Query Biased Snippet Generation
    Tsegay, Y ; Puglisi, SJ ; Turpin, A ; Zobel, J ; Boughanem, M ; Berrut, C ; Mothe, J ; SouleDupuy, C (SPRINGER-VERLAG BERLIN, 2009)
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    Examining the pseudo-standard web search engine results page
    Turpin, A ; Billerbeck, B ; Scholer, F ; Abel, LA (Queensland University of Technology, 2006-12-01)
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    Efficient plagiarism detection for large code repositories
    Burrows, S ; Tahaghoghi, SMM ; Zobel, J (WILEY, 2007-02)
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    Goal-directed automated negotiation for supporting mobile user coordination
    Rahwan, I ; Koch, F ; Graham, C ; Kattan, A ; Sonenberg, L ; Dey, A ; Kokinov, B ; Leake, D ; Turner, R (SPRINGER-VERLAG BERLIN, 2005)
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    Federating distributed clinical data for the prediction of adverse hypotensive events
    Stell, A ; Sinnott, R ; Jiang, J ; Donald, R ; Chambers, I ; Citerio, G ; Enblad, P ; Gregson, B ; Howells, T ; Kiening, K ; Nilsson, P ; Ragauskas, A ; Sahuquillo, J ; Piper, I (Royal Society, The, 2009)
    The ability to predict adverse hypotensive events, where a patient's arterial blood pressure drops to abnormally low (and dangerous) levels, would be of major benefit to the fields of primary and secondary health care, and especially to the traumatic brain injury domain. A wealth of data exist in health care systems providing information on the major health indicators of patients in hospitals (blood pressure, temperature, heart rate, etc.). It is believed that if enough of these data could be drawn together and analysed in a systematic way, then a system could be built that will trigger an alarm predicting the onset of a hypotensive event over a useful time scale, e.g. half an hour in advance. In such circumstances, avoidance measures can be taken to prevent such events arising. This is the basis for the Avert-IT project (http://www.avert-it.org), a collaborative EU-funded project involving the construction of a hypotension alarm system exploiting Bayesian neural networks using techniques of data federation to bring together the relevant information for study and system development.
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    Redundant documents and search effectiveness
    Bernstein, Y ; Zobel, J (ACM, 2005-12-01)
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    Using query logs to establish vocabularies in distributed information retrieval
    Shokouhi, M ; Zobel, J ; Tahaghoghi, S ; Scholer, F (ELSEVIER SCI LTD, 2007-01)
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    Aggregated click-through data in a homogeneous user community
    Wu, M ; Turpin, A ; Zobel, J (ACM, 2008-12-15)
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    Robust Result Merging Using Sample-Based Score Estimates
    Shokouhi, M ; Zobel, J (ASSOC COMPUTING MACHINERY, 2009)
    In federated information retrieval, a query is routed to multiple collections and a single answer list is constructed by combining the results. Such metasearch provides a mechanism for locating documents on the hidden Web and, by use of sampling, can proceed even when the collections are uncooperative. However, the similarity scores for documents returned from different collections are not comparable, and, in uncooperative environments, document scores are unlikely to be reported. We introduce a new merging method for uncooperative environments, in which similarity scores for the sampled documents held for each collection are used to estimate global scores for the documents returned per query. This method requires no assumptions about properties such as the retrieval models used. Using experiments on a wide range of collections, we show that in many cases our merging methods are significantly more effective than previous techniques.