Neural Networks for Proof-Pattern Recognition

Ekaterina Komendantskaya, Kacper Lichota

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We propose a new method of feature extraction that allows to apply pattern-recognition abilities of neural networks to data-mine automated proofs. We propose a new algorithm to represent proofs for first-order logic programs as feature vectors; and present its implementation. We test the method on a number of problems and implementation scenarios, using three-layer neural nets with backpropagation learning.
Original languageEnglish
Title of host publicationArtificial Neural Networks and Machine Learning – ICANN 2012
Subtitle of host publication22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II
EditorsAlessandro E. P. Villa, Włodzisław Duch, Péter Érdi, Francesco Masulli, Günther Palm
PublisherSpringer
Pages427-434
Number of pages8
ISBN (Electronic)9783642332661
ISBN (Print)9783642332654
DOIs
Publication statusPublished - 2012

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume7553
ISSN (Print)0302-9743

Fingerprint

Pattern recognition
Neural networks
Backpropagation
Feature extraction

Keywords

  • Machine learning
  • pattern-recognition
  • data mining
  • neural networks
  • first-order logic programs
  • automated proofs

Cite this

Komendantskaya, E., & Lichota, K. (2012). Neural Networks for Proof-Pattern Recognition. In A. E. P. Villa, W. Duch, P. Érdi, F. Masulli, & G. Palm (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II (pp. 427-434). (Lecture Notes in Computer Science; Vol. 7553). Springer. https://doi.org/10.1007/978-3-642-33266-1_53
Komendantskaya, Ekaterina ; Lichota, Kacper. / Neural Networks for Proof-Pattern Recognition. Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II. editor / Alessandro E. P. Villa ; Włodzisław Duch ; Péter Érdi ; Francesco Masulli ; Günther Palm. Springer, 2012. pp. 427-434 (Lecture Notes in Computer Science).
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keywords = "Machine learning, pattern-recognition, data mining, neural networks, first-order logic programs, automated proofs",
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Komendantskaya, E & Lichota, K 2012, Neural Networks for Proof-Pattern Recognition. in AEP Villa, W Duch, P Érdi, F Masulli & G Palm (eds), Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II. Lecture Notes in Computer Science, vol. 7553, Springer, pp. 427-434. https://doi.org/10.1007/978-3-642-33266-1_53

Neural Networks for Proof-Pattern Recognition. / Komendantskaya, Ekaterina; Lichota, Kacper.

Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II. ed. / Alessandro E. P. Villa; Włodzisław Duch; Péter Érdi; Francesco Masulli; Günther Palm. Springer, 2012. p. 427-434 (Lecture Notes in Computer Science; Vol. 7553).

Research output: Chapter in Book/Report/Conference proceedingChapter

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T1 - Neural Networks for Proof-Pattern Recognition

AU - Komendantskaya, Ekaterina

AU - Lichota, Kacper

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AB - We propose a new method of feature extraction that allows to apply pattern-recognition abilities of neural networks to data-mine automated proofs. We propose a new algorithm to represent proofs for first-order logic programs as feature vectors; and present its implementation. We test the method on a number of problems and implementation scenarios, using three-layer neural nets with backpropagation learning.

KW - Machine learning

KW - pattern-recognition

KW - data mining

KW - neural networks

KW - first-order logic programs

KW - automated proofs

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DO - 10.1007/978-3-642-33266-1_53

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BT - Artificial Neural Networks and Machine Learning – ICANN 2012

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Komendantskaya E, Lichota K. Neural Networks for Proof-Pattern Recognition. In Villa AEP, Duch W, Érdi P, Masulli F, Palm G, editors, Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II. Springer. 2012. p. 427-434. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-33266-1_53