ICSE 2009 and WSDM 2009

31 01 2009

Great news! Recently, two papers in which I was involved got accepted:

M. Wermelinger, Y. Yu and M. Strohmaier, Using Formal Concept Analysis to Construct and Visualise Social Hierarchies of Software Developers, International Conference on Software Engineering, Vancouver (ICSE’09), New Ideas and Emerging Results Track (4 page Poster Paper), Vancouver, Canada, 2009.

Update: Michel has posted an announcement on his blog as well (including a link to the submitted version).

Summary: Interest in the human aspects of software engineering has grown in the past years. For example, based on activity logs in software artefact repositories, researchers are recommending who should fix a bug for a certain component. However, existing work largely follows ad-hoc approaches to relate software artefacts to developers and rarely makes those socio-technical relations explicit in a single structure. In this paper we propose a novel application of formal concept analysis, in order to overcome those deficiencies. As a case study, we construct and visualise different views of the developers who fix and discuss bugs in the Eclipse project.

M. Strohmaier, M. Kroell, C. Koerner, Intentional Query Suggestion: Making User Goals More Explicit During Search, Workshop on Web Search Click Data WSCD’09, in conjunction with WSDM 2009, Barcelona, Spain, 2009. (pdf)

Abstract: The degree to which users’ make their search intent explicit can be assumed to represent an upper bound on the level of service that search engines can provide. In a departure from traditional query expansion mechanisms, we introduce Intentional Query Suggestion as a novel idea that is attempting to make users’ intent more explicit during search. In this paper, we present a prototypical algorithm for Intentional Query Suggestion and we discuss corresponding data from comparative experiments with traditional query suggestion mechanisms. Our preliminary results indicate that intentional query suggestions 1) diversify search result sets (i.e. it reduces result set overlap) and 2) have the potential to yield higher click-through rates than traditional query suggestions.




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