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Top-k Shortest Paths in Directed Labeled Multigraphs

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 641))

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Abstract

A top-k shortest path algorithm finds the k shortest paths of a given graph ordered by length. Interpreting graphs as RDF may lead to additional constraints, such as special loop restrictions or path patterns. Thus, traditional algorithms such as the ones by Dijkstra, Yen or Eppstein cannot be applied without further ado. We therefore implemented a solution method based on Eppstein’s algorithm which is thoroughly discussed in this paper. Using this method we were able to solve all tasks of the ESWC 2016 Top-k Shortest Path Challenge while achieving only moderate overhead compared to the original version. However, we also identified some potential for improvements. Additionally, a concept for embedding our algorithm into a SPARQL endpoint is provided.

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Notes

  1. 1.

    This is done since providing a literal as a target node could be ambiguous (e.g. several persons having the same first name). Thus, to apply our algorithm in such use cases, this ambiguity has to be resolved first. For example, one could first search all resources associated with the given literal and then choose the one that is actually meant as the target node (or subsequently run the algorithm on all of them).

  2. 2.

    In particular, we found unparsable datatypes like <http://dbpedia.org/datatype/brake horsepower>. Our first solution removed them, in a later version they were fixed by URL-encoding the blank.

  3. 3.

    Our algorithm is still implemented as a single thread application.

  4. 4.

    Given two resources A and B, A as the source and B as the target, the corresponding SPARQL query is A !:* B. Technically, this searches for zero or more occurrences of properties (indicated by “*”) between A and B not (“!”) matching an introduced fake IRI “:”.

  5. 5.

    https://jena.apache.org/documentation/query/arq-query-eval.html.

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Acknowledgement

This work was partially funded by the BMBF project Multimedia Opinion Mining (MOM: 01WI15002).

Author information

Authors and Affiliations

  1. Knowledge Management Group, German Research Center for Artificial Intelligence (DFKI) GmbH, Trippstadter Straße 122, Kaiserslautern, Germany

    Sven Hertling, Markus Schröder, Christian Jilek & Andreas Dengel

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

Authors
  1. Sven Hertling
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  2. Markus Schröder
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  3. Christian Jilek
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  4. Andreas Dengel
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Corresponding author

Correspondence to Sven Hertling .

Editor information

Editors and Affiliations

  1. IT Systems Engineering, Hasso-Plattner Institute, Potsdam, Germany

    Harald Sack

  2. Leibniz Universität Hannover , Hannover, Germany

    Stefan Dietze

  3. Elsevier B.V. , Amsterdem, The Netherlands

    Anna Tordai

  4. Universität Bonn , Bonn, Germany

    Christoph Lange

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Hertling, S., Schröder, M., Jilek, C., Dengel, A. (2016). Top-k Shortest Paths in Directed Labeled Multigraphs. In: Sack, H., Dietze, S., Tordai, A., Lange, C. (eds) Semantic Web Challenges. SemWebEval 2016. Communications in Computer and Information Science, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-46565-4_16

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  • DOI: https://doi.org/10.1007/978-3-319-46565-4_16

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