Ranking distributed knowledge repositories

  • Authors:

  • Robert Neumayer;Krisztian Balog;Kjetil Nørvåg

  • Affiliations:

  • Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

  • Venue:
  • TPDL'12 Proceedings of the Second international conference on Theory and Practice of Digital Libraries
  • Year:
  • 2012

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Abstract

Increasingly many knowledge bases are published as Linked Data, driving the need for effective and efficient techniques for information access. Knowledge repositories are naturally organised around objects or entities and constitute a promising data source for entity-oriented search. There is a growing body of research on the subject, however, it is almost always (implicitly) assumed that a centralised index of all data is available. In this paper, we address the task of ranking distributed knowledge repositories--a vital component of federated search systems--and present two probabilistic methods based on generative language modeling techniques. We present a benchmarking testbed based on the test suites of the Semantic Search Challenge series to evaluate our approaches. In our experiments, we show that both our ranking approaches provide competitive performance and offer a viable alternative to centralised retrieval.