Reachability Analysis of Graph Modelled Collections

  • Serwah Sabetghadam
  • Mihai Lupu
  • Ralf Bierig
  • Andreas Rauber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9022)


This paper is concerned with potential recall in multimodal information retrieval in graph-based models. We provide a framework to leverage individuality and combination of features of different modalities through our formulation of faceted search. We employ a potential recall analysis on a test collection to gain insight on the corpus and further highlight the role of multiple facets, relations between the objects, and semantic links in recall improvement. We conduct the experiments on a multimodal dataset containing approximately 400,000 documents and images. We demonstrate that leveraging multiple facets increases most notably the recall for very hard topics by up to 316%.


Semantic Relation Spreading Activation Image Search Relevant Object Reachability Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Serwah Sabetghadam
    • 1
  • Mihai Lupu
    • 1
  • Ralf Bierig
    • 1
  • Andreas Rauber
    • 1
  1. 1.Institute of Software Technology and Interactive SystemsVienna University of TechnologyViennaAustria

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