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2019 | OriginalPaper | Chapter

Towards Understanding Classification and Identification

Authors : Mattia Fumagalli, Gábor Bella, Fausto Giunchiglia

Published in: PRICAI 2019: Trends in Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

The paper focuses on two pivotal cognitive functions of both natural and AI agents, namely classification and identification. Inspired from the theory of teleosemantics, itself based on neuroscientific results, we show that these two functions are complementary and rely on distinct forms of knowledge representation. We provide a new perspective on well-known AI techniques by categorising them as either classificational or identificational. Our proposed Teleo-KR architecture provides a high-level framework for combining the two functions within a single AI system. As validation and demonstration on a concrete application, we provide experiments on the large-scale reuse of classificational (ontological) knowledge for the purposes of learning-based schema identification.

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https://lov.linkeddata.es.

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Baader, F.: The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)MATH

Bader, S., Hitzler, P.: Dimensions of Neural-Symbolic Integration–a Structured Survey. arXiv preprint cs/0511042 (2005)

Barsalou, L.W.: Perceptual symbol systems. Behav. Brain Sci. 22, 577–660 (1999)

Bella, G., et al.: Language and domain aware lightweight ontology matching. J. Web Semant. 43, 1–17 (2017)CrossRef

Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, New York (2006)MATH

Brachman, R.J., Schmolze, J.G.: An overview of the KL-ONE knowledge representation system. In: Readings in Artificial Intelligence and Databases, pp. 207–230. Morgan Kaufmann, Burlington (1989)

Brickley, D., Miller, L.: FOAF vocabulary specification 0.91 (2010)

Buitelaar, P., Cimiano, P., Magnini, B.: Ontology learning from text: an overview. In: Ontology Learning from Text: Methods, Evaluation and Applications, vol. 123, pp. 3–12 (2005)

Domingos, P.: Structured machine learning: ten problems for the next ten years. In: Proceedings of the Annual International Conference on Inductive Logic Programming (2007)

10.

Euzenat, J., Shvaiko, P.: Ontology Matching, vol. 18. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-49612-0MATHCrossRef

11.

Evans, G., McDowell, J.: The Varieties of Reference. Clarendon Press (1982)

12.

Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L.: Sweetening ontologies with DOLCE. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 166–181. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45810-7_18MATHCrossRef

13.

Getoor, L., Taskar, B.: Introduction to Statistical Relational Learning. MIT Press, Cambridge (2007)MATHCrossRef

14.

Giunchiglia, F., Fumagalli, M.: Concepts as (recognition) abilities. In: FOIS (2016)

15.

Guarino, N., Welty, C.: Evaluating ontological decisions with OntoClean. Commun. ACM 45(2), 61–65 (2002)CrossRef

16.

Hinton, G.: Learning multiple layers of representation. Trends Cogn. Sci. 11(10), 428–434 (2007)CrossRef

17.

da Cunha Lamb, L.: The grand challenges and myths of neural-symbolic computation. In: Dagstuhl Seminar 08041. Recurrent Neural Networks-Models, Capacities, and Applications. Schloss Dagstuhl, Dagstuhl (2008)

18.

Macdonald, G., Papineau, D., et al.: Teleosemantics. Oxford University Press, Oxford (2006)

19.

McNeill, F., Bundy, A.: Dynamic, automatic, first-order ontology repair by diagnosis of failed plan execution. IJSWIS 3(3), 1–35 (2007)

20.

Millikan, R.G.: On Clear and Confused Ideas: An Essay About Substance Concepts. Cambridge University Press, Cambridge (2000)CrossRef

21.

Millikan, R.G.: Language: A Biological Model. Oxford University Press, Oxford (2005)CrossRef

22.

Millikan, R.G.: Learning Language. Published in German translation by Alex Burri as ‘Spracherwerb’. Biosemantik. Sprachphilosophische Aufsätze, pp. 85–115. Surkamp, Berlin (2012)

23.

Millikan, R.G.: Beyond Concepts: Unicepts, Language, and Natural Information. Oxford University Press, Oxford (2017)CrossRef

24.

Muggleton, S., De Raedt, L.: Inductive logic programming: theory and methods. J. Logic Program. 19, 629–679 (1994)MathSciNetMATHCrossRef

25.

O’Reilly, R.C.: Six principles for biologically based computational models of cortical cognition. Trends Cogn. Sci. 2(11), 455–462 (1998)CrossRef

26.

Ritze, D., et al.: Linguistic analysis for complex ontology matching. In: CEUR Workshop Proceedings, vol. 689. RWTH (2010)

27.

Rosch, E.: Principles of categorization. In: Concepts: Core Readings, vol. 189 (1999)

28.

Smith, L.B.: Learning to recognize objects. Psychol. Sci. 14(3), 244–250 (2003)CrossRef

29.

Sarker, M.K., et al.: Explaining Trained Neural Networks with Semantic Web Technologies: First Steps. arXiv preprint. arXiv: 1710.04324 (2017)

30.

Sleeman, J., et al.: Entity type recognition for heterogeneous semantic graphs. AI Mag. 36(1), 75–86 (2015)CrossRef

Title: Towards Understanding Classification and Identification
Authors: Mattia Fumagalli
Gábor Bella
Fausto Giunchiglia
Publisher: Springer International Publishing
Book: PRICAI 2019: Trends in Artificial Intelligence
Print ISBN: 978-3-030-29907-1

Electronic ISBN: 978-3-030-29908-8

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-29908-8_6

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