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Design and Use of a Semantic Similarity Measure for Interoperability Among Agents

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Multiagent System Technologies (MATES 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9872))

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Abstract

The capability to identify the sense of polysemic words, i.e. words that have multiple meanings, is an essential part of intelligent systems, e.g. when updating an agent’s beliefs during conversations. This process is also called Word Sense Disambiguation and is approached by applying semantic similarity measures. Within this work, we present an algorithm to create such a semantic similarity measure using marker passing, that: (1) generates a semantic network out of a concepts used e.g. in semantic service descriptions, (2) sends markers through the networks to tag sub-graphs that are of relevance, and (3) uses these markers to create a semantic similarity measure. We will discuss the properties of the algorithm, elaborate its performance, and discuss the lifted properties for the algorithm to be used in WSD. To evaluate our approach, we compare it to state of the art measures using the Rubinstein1965 dataset. It is shown, that our approach outperforms these state of the art measures.

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Notes

  1. 1.

    Sometimes referred to as Activation Spreading or Token Passing.

  2. 2.

    Implementation available at: https://gitlab.tubit.tu-berlin.de/johannes_faehndrich/semantic-decomposition. For access contact the first author.

  3. 3.

    Even with contextual information such concepts are not always easy to identify, as shown by Bar-Hillel [3], e.g. “The box is in the pen”.

  4. 4.

    With less symbolic information the marker passing becomes activation spreading, which in the special case of artificial neuronal networks is subject to research.

  5. 5.

    http://projects.csail.mit.edu/jwi/.

  6. 6.

    https://www.ukp.tu-darmstadt.de/software/jwktl/.

  7. 7.

    https://dumps.wikimedia.org/ downloaded on 2015.12.19.

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Author information

Authors and Affiliations

  1. DAI-Laboratory, Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Ernst-Reuter-Platz 7, 10587, Berlin, Germany

    Johannes Fähndrich, Sabine Weber & Sebastian Ahrndt

Authors
  1. Johannes Fähndrich
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  2. Sabine Weber
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  3. Sebastian Ahrndt
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Corresponding author

Correspondence to Johannes Fähndrich .

Editor information

Editors and Affiliations

  1. DFKI , Saarbrücken, Germany

    Matthias Klusch

  2. Institute for Computer Science &, University of Duisburg-Essen Institute for Computer Science &, Essen, Nordrhein-Westfalen, Germany

    Rainer Unland

  3. IBM Haifa Research Lab , Haifa, Israel

    Onn Shehory

  4. University of Hamburg VSIS, Hamburg, Hamburg, Germany

    Alexander Pokahr

  5. Distributed Artificial Intelligence, Technical University of Berlin Distributed Artificial Intelligence, Berlin, Berlin, Germany

    Sebastian Ahrndt

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Fähndrich, J., Weber, S., Ahrndt, S. (2016). Design and Use of a Semantic Similarity Measure for Interoperability Among Agents. In: Klusch, M., Unland, R., Shehory, O., Pokahr, A., Ahrndt, S. (eds) Multiagent System Technologies. MATES 2016. Lecture Notes in Computer Science(), vol 9872. Springer, Cham. https://doi.org/10.1007/978-3-319-45889-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-45889-2_4

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