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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-44853

Stutz, P; Bernstein, A; Cohen, W W (2010). Signal/Collect: graph algorithms for the (Semantic) Web. In: ISWC 2010, Shanghai, China, 7 November 2010 - 11 November 2010, -764.

Accepted Version


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 paper 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 prototype Signal/Collect framework that executes algorithms in our programming model. We empirically show that this prototype transparently scales and that guiding computations by scoring as well as asynchronicity can greatly improve the convergence of some example algorithms. We released the framework under the Apache License 2.0 (at http://www.ifi.uzh.ch/ddis/research/sc).



208 downloads since deposited on 24 Feb 2011
25 downloads since 12 months

Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Event End Date:11 November 2010
Deposited On:24 Feb 2011 15:57
Last Modified:05 Apr 2016 14:44
Other Identification Number:1450

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