Neural Networks for Proof-Pattern Recognition

Ekaterina Komendantskaya; Kacper Lichota

doi:10.1007/978-3-642-33266-1_53

Neural Networks for Proof-Pattern Recognition

Ekaterina Komendantskaya, Kacper Lichota

Research output: Chapter in Book/Report/Conference proceeding › Chapter

1 Citation (Scopus)

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 language	English
Title of host publication	Artificial Neural Networks and Machine Learning – ICANN 2012
Subtitle of host publication	22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II
Editors	Alessandro E. P. Villa, Włodzisław Duch, Péter Érdi, Francesco Masulli, Günther Palm
Publisher	Springer
Pages	427-434
Number of pages	8
ISBN (Electronic)	9783642332661
ISBN (Print)	9783642332654
DOIs	https://doi.org/10.1007/978-3-642-33266-1_53
Publication status	Published - 2012

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Berlin Heidelberg
Volume	7553
ISSN (Print)	0302-9743

Keywords

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

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

http://www.scopus.com/inward/record.url?scp=84867678467&partnerID=8YFLogxK

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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title = "Neural Networks for Proof-Pattern Recognition",

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.",

keywords = "Machine learning, pattern-recognition, data mining, neural networks, first-order logic programs, automated proofs",

author = "Ekaterina Komendantskaya and Kacper Lichota",

year = "2012",

doi = "10.1007/978-3-642-33266-1_53",

language = "English",

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booktitle = "Artificial Neural Networks and Machine Learning – ICANN 2012",

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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 proceeding › Chapter

TY - CHAP

T1 - Neural Networks for Proof-Pattern Recognition

AU - Komendantskaya, Ekaterina

AU - Lichota, Kacper

PY - 2012

Y1 - 2012

N2 - 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.

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

U2 - 10.1007/978-3-642-33266-1_53

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

M3 - Chapter

SN - 9783642332654

T3 - Lecture Notes in Computer Science

SP - 427

EP - 434

BT - Artificial Neural Networks and Machine Learning – ICANN 2012

A2 - Villa, Alessandro E. P.

A2 - Duch, Włodzisław

A2 - Érdi, Péter

A2 - Masulli, Francesco

A2 - Palm, Günther

PB - Springer

ER -

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). doi: 10.1007/978-3-642-33266-1_53

Neural Networks for Proof-Pattern Recognition

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