Voting for candidates: adapting data fusion techniques for an expert search task

In an expert search task, the users' need is to identify people who have relevant expertise to a topic of interest. An expert search system predicts and ranks the expertise of a set of candidate persons with respect to the users' query. In this paper, we propose a novel approach for predicting and ranking candidate expertise with respect to a query. We see the problem of ranking experts as a voting problem, which we model by adapting eleven data fusion techniques.We investigate the effectiveness of the voting approach and the associated data fusion techniques across a range of document weighting models, in the context of the TREC 2005 Enterprise track. The evaluation results show that the voting paradigm is very effective, without using any collection specific heuristics. Moreover, we show that improving the quality of the underlying document representation can significantly improve the retrieval performance of the data fusion techniques on an expert search task. In particular, we demonstrate that applying field-based weighting models improves the ranking of candidates. Finally, we demonstrate that the relative performance of the adapted data fusion techniques for the proposed approach is stable regardless of the used weighting models

Using relevance feedback in expert search

In Enterprise settings, expert search is considered an important task. In this search task, the user has a need for expertise - for instance, they require assistance from someone about a topic of interest. An expert search system assists users with their "expertise need" by suggesting people with relevant expertise to the topic of interest. In this work, we apply an expert search approach that does not explicitly rank candidates in response to a query, but instead implicitly ranks candidates by taking into account a ranking of document with respect to the query topic. Pseudo-relevance feedback, aka query expansion, has been shown to improve retrieval performance in adhoc search tasks. In this work, we investigate to which extent query expansion can be applied in an expert search task to improve the accuracy of the generated ranking of candidates. We define two approaches for query expansion, one based on the initial of ranking of documents for the query topic. The second approach is based on the final ranking of candidates. The aims of this paper are two-fold. Firstly, to determine if query expansion can be successfully applied in the expert search task, and secondly, to ascertain if either of the two forms of query expansion can provide robust, improved retrieval performance. We perform a thorough evaluation contrasting the two query expansion approaches in the context of the TREC 2005 and 2006 Enterprise tracks

Combining fields in known-item email search

Emails are examples of structured documents with various fields. These fields can be exploited to enhance the retrieval effectiveness of an Information Retrieval (IR) system that mailing list archives. In recent experiments of the TREC2005 Enterprise track, various fields were applied to varying degrees of success by the participants. In his work, using a field-based weighting model, we investigate the retrieval performance attainable by each field, and examine when fields evidence should be combined or not

Land use change detection with Landsat-2 data for monitoring and predicting regional water quality degradation

There are no author-identified significant results in this report

Calculus on surfaces with general closest point functions

The Closest Point Method for solving partial differential equations (PDEs) posed on surfaces was recently introduced by Ruuth and Merriman [J. Comput. Phys. 2008] and successfully applied to a variety of surface PDEs. In this paper we study the theoretical foundations of this method. The main idea is that surface differentials of a surface function can be replaced with Cartesian differentials of its closest point extension, i.e., its composition with a closest point function. We introduce a general class of these closest point functions (a subset of differentiable retractions), show that these are exactly the functions necessary to satisfy the above idea, and give a geometric characterization this class. Finally, we construct some closest point functions and demonstrate their effectiveness numerically on surface PDEs

Log::ProgramInfo: A Perl module to collect and log data for bioinformatics pipelines.

BackgroundTo reproduce and report a bioinformatics analysis, it is important to be able to determine the environment in which a program was run. It can also be valuable when trying to debug why different executions are giving unexpectedly different results.ResultsLog::ProgramInfo is a Perl module that writes a log file at the termination of execution of the enclosing program, to document useful execution characteristics. This log file can be used to re-create the environment in order to reproduce an earlier execution. It can also be used to compare the environments of two executions to determine whether there were any differences that might affect (or explain) their operation.AvailabilityThe source is available on CPAN (Macdonald and Boutros, Log-ProgramInfo. http://search.cpan.org/~boutroslb/Log-ProgramInfo/).ConclusionUsing Log::ProgramInfo in programs creating result data for publishable research, and including the Log::ProgramInfo output log as part of the publication of that research is a valuable method to assist others to duplicate the programming environment as a precursor to validating and/or extending that research

Review of the environmental and organisational implications of cloud computing: final report.

Cloud computing – where elastic computing resources are delivered over the Internet by external service providers – is generating significant interest within HE and FE. In the cloud computing business model, organisations or individuals contract with a cloud computing service provider on a pay-per-use basis to access data centres, application software or web services from any location. This provides an elasticity of provision which the customer can scale up or down to meet demand. This form of utility computing potentially opens up a new paradigm in the provision of IT to support administrative and educational functions within HE and FE. Further, the economies of scale and increasingly energy efficient data centre technologies which underpin cloud services means that cloud solutions may also have a positive impact on carbon footprints. In response to the growing interest in cloud computing within UK HE and FE, JISC commissioned the University of Strathclyde to undertake a Review of the Environmental and Organisational Implications of Cloud Computing in Higher and Further Education [19]

Evaluation of Ankom F58 Filter Bags Compared to Dacron Bags and Beakers for Analysis of Acid Detergent Fiber

Feed and fecal samples were analyzed to compare three methods of determining acid detergent fiber. Each sample was weighed into both Dacron and Ankom F58 fiber bags and then analyzed using an Ankom fiber analyzer. Results were then compared to the Van Soest beaker method. Ankom F58 bags helped reduce washout of small particles associated with Dacron bags, but fecal samples needed to be incubated in detergent for an extended amount of time to isolate acid detergent fiber material. Utilizing a technique that produces correct acid detergent fiber values is important for producers because these values are used as a proxy for calculating total digestible nutrients of feedstuffs