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Completed research project

Title / Titel Signal / Collect: Graph Algorithms for the (Semantic) Web
PDF Abstract (PDF, 14 KB)
Summary / Zusammenfassung The Semantic Web graph is growing at an incredible pace, enabling opportunities to discover new knowledge by interlinking and analyzing previously unconnected data sets. This confronts researchers with a conundrum: Whilst the data is available the programming models that facilitate scalability and the infrastructure to run various algorithms on the graph are missing.
Some use MapReduce – a good solution for many problems. However, even some simple iterative graph algorithms do not map nicely to that programming model requiring programmers to shoehorn their problem to the MapReduce model.

This projects presents the Signal/Collect programming model for synchronous and asynchronous graph algorithms. We demonstrate that this abstraction can capture the essence of many algorithms on graphs in a concise and elegant way by giving Signal/Collect adaptations of various relevant algorithms. Furthermore, we built and evaluated a pro- totype Signal/Collect framework that executes algorithms in our pro- gramming model. We empirically show that this prototype transpar- ently scales and that guiding computations by scoring as well as asynchronicity can greatly improve the convergence of some example algo- rithms.
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Publications / Publikationen Philip Stutz, Abraham Bernstein, William W. Cohen, Signal/Collect: Graph Algorithms for the (Semantic) Web, ISWC 2010, Editor(s): P.F. Patel-Schneider; 2010, Springer, Heidelberg.

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Project leadership and contacts /
Projektleitung und Kontakte
Prof. Abraham Bernstein, Ph.D. (Project Leader)
Funding source(s) /
Unterstützt durch
Universität Zürich (position pursuing an academic career), Foundation
In collaboration with /
In Zusammenarbeit mit
William Cohen, Machine Learning Department, Carnegie Mellon University United States
Duration of Project / Projektdauer Jan 2010 to Dec 2015