Formal Language Decomposition into Semantic Primes

Abstract

This paper describes an algorithm for semantic decomposition. For that we surveys languages used to enrich contextual information with semantic descriptions. Such descriptions can be e.g. applied to enable reasoning when collecting vast amounts of information. In particular, we focus on the elements of the languages that make up their semantic. To do so, we compare the expressiveness of the well-known languages OWL, PDDL and MOF with a theory from linguistic called the Natural Semantic Metalanguage. We then analyze how the semantic of the language is build up and describe how semantic decomposition based on the semantic primes can be used for a so called mental lexicon. This mental lexicon can be used to reason upon semantic service description in the research domain of service match making.
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Bikakis, A. et al., 2008. A Survey of Semantics-Based Approaches for Context Reasoning in Ambient Intelligence,

Braubach, L., Pokahr, A. & Moldt, D., 2005. Goal representation for BDI agent systems. multi-agent systems, pp.44–65.

Brennan, S.E., 1998. The grounding problem in conversations with and through computers. Social and cognitive approaches to interpersonal …, pp.201–225. Available at: http://www.psychology.stonybrook.edu/sbrennan-/papers/brenfuss.pdf.

Burke, E.K. et al., 2013. Hyper-heuristics: a survey of the state of the art. Journal of the Operational Research Society, 64(12), pp.1695–1724.

Chen, H., Finin, T. & Joshi, A., 2003. An ontology for context-aware pervasive computing environments. The Knowledge Engineering Review, 18(3), pp.197–207.

Colombetti, M. & Verdicchio, M., 2002. An analysis of agent speech acts as institutional actions, New York, New York, USA: ACM.

Duda, R.O., Hart, P.E. & Stork, D.G., 2001. Pattern classification Second, Wiley-Interscience, New York.

Favre, J.M., 2004. Towards a basic theory to model model driven engineering, 3rd Workshop in Software Model Engineering.

Fähndrich, J., Ahrndt, S. & Albayrak, S., 2013. Self-Explaining Agents. Jurnal Teknologi (Science & Engineering), 63(3), pp.53–64.

Fox, M. & Long, D., 2003. PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains. 20, pp.61–124.

Gal, A. et al., 2005. Automatic Ontology Matching Using Application Semantics. pp.1–12.

Goddard, C., 2008. Cross-linguistic Semantics, John Benjamins Publishing.

Goddard, C., 2010. Semantic molecules and semantic complexity:(with special reference to“ environmental” molecules). 8(1), pp.123–155.

Goddard, C. & Wierzbicka, A., 1994. Semantic and Lexical Universals, John Benjamins Publishing.

Grau, B.C. et al., 2008. OWL 2: The next step for OWL. Web Semantics: Science, Services and Agents on the World Wide Web, 6(4), pp.309–322.

Gruber, T., 2008. Encyclopedia of database systems L. Liu & T. Ozsu, eds. Encyclopedia of Database Systems.

Gupta, N. & Nau, D.S., 1992. On the Complexity of Blocks-World Planning. 56(2--3), pp.223–254.

Heim, I., 2008. Decomposing antonyms. In Proceedings of Sinn und Bedeutung.

Henricksen, K. & Indulska, J., 2004. Modelling and using imperfect context information. Audio, Transactions of the IRE Professional Group on, pp.33–37.

Horrocks, I. et al., 2004. SWRL: A Semantic Web Rule Language Combining OWL and RuleML, W3C Member Submission.

Klir, G.J. & Yuan, B., 1995. Fuzzy Sets and Fuzzy Logic: Theory and Applications, Upper Saddle River, NJ, USA: Prentice-Hall, Inc.

Lassila, O. & Swick, R.R., 1999. Resource description framework (RDF) model and syntax specification.

McDermott, D.V., 2003. The Formal Semantics of Processes in PDDL.

McGuinness, D.L., Van Harmelen, F.others, 2004. OWL web ontology language overview. W3C recommendation, 10(2004-03), p.10.

Mel’?uk, I. & Wanner, L., 1996. Lexical functions and lexical inheritance for emotion lexemes in German. Lexical functions in lexicography and natural language processing. Amsterdam/Philadelphia. John Benjamin, pp.209–278.

Mel’?uk, I. (2006). Explanatory combinatorial dictionary. Open problems in linguistics and lexicography, pp. 225-355.

Mengen, G.D.T.U., 1994. Fuzzy Decision Support-Systeme.

Novák, V., 2001. Antonyms and linguistic quantiers in fuzzy logic. Journal of Web Seamantics, 124(3), pp.335–351. Available at: http://www.sciencedirect.com/science/article/pii/S016501140100104X.

Ruiz-Mirazo, K., Peretó, J. & Moreno, A., 2004. A Universal Definition of Life: Autonomy and Open-Ended Evolution. Origins of life and evolution of the biosphere, 34(3), pp.323–346.

Salehie, M. & Tahvildari, L., 2009. Self-adaptive software: Landscape and research challenges. 4(2), pp.1–42.

Smith, J. et al., 2000. Category theoretic approaches of representing precise UML semantics. Available at: http://www.ccs.neu.edu/home/kenb/pub/2000/03/public.pdf.

Sternberg, R.J. & Clarke, A.M., 1986. Beyond IQ: A Triarchic Theory of Human Intelligence. British Journal of Educational Studies, 34(2), p.205.

Stoilos, G. et al., 2005. Fuzzy OWL: Uncertainty and the Semantic Web. OWLED.

Usón, R.M. & Faber, P., 2005. Decomposing semantic decomposition: Towards a semantic metalanguage in RRG. pp.1–28.

van der Hoek, W., 2004. Epistemic logic for AI and computer science, Cambridge University Press.

Walter, E., 2008. Cambridge advanced learner's dictionary, Ernst Klett Sprachen. Available at: http://dictionary.cambridge.org/dictionary/british/.

Wierzbicka, A., 2006. English : Meaning and Culture. pp.1–363.

Wierzbicka, A., 2009. Mental Lexicon. In Berlin: Mouton de Gruyter.

Wierzbicka, A., 1996. Semantics: Primes and Universals, Oxford University Press, USA.
FÄhndrich, J., Ahrndt, S., & Albayrak, S. (2014). Formal Language Decomposition into Semantic Primes. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 3(1), 56–73. https://doi.org/10.14201/ADCAIJ2014385673

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Author Biographies

Johannes FÄhndrich

,
Technische Universität Berlin
DAI-Labor Technische Universität Berlin Fakultät IV – Elektrotechnik & Informatik Sekretariat TEL 14 Ernst-Reuter-Platz 7 10587 Berlin, Germany

Sebastian Ahrndt

,
Technische Universität Berlin
DAI-Labor Technische Universität Berlin Fakultät IV – Elektrotechnik & Informatik Sekretariat TEL 14 Ernst-Reuter-Platz 7 10587 Berlin, Germany

Sahin Albayrak

,
Technische Universität Berlin
DAI-Labor Technische Universität Berlin Fakultät IV – Elektrotechnik & Informatik Sekretariat TEL 14 Ernst-Reuter-Platz 7 10587 Berlin, Germany
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