**Neural networks for proof-pattern recognition.** / Komendantskaya, Ekaterina; Lichota, Kacper.

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

Komendantskaya, E & Lichota, K 2012, Neural networks for proof-pattern recognition. in AEP Villa, W Duch, P Erdi, 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 , Berlin, pp. 427-434, 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, 11-14 September. DOI: 10.1007/978-3-642-33266-1_53

Komendantskaya, E., & Lichota, K. (2012). Neural networks for proof-pattern recognition. In A. E. P. Villa, W. Duch, P. Erdi, 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). Berlin: Springer . DOI: 10.1007/978-3-642-33266-1_53

Komendantskaya E, Lichota K. Neural networks for proof-pattern recognition. In Villa AEP, Duch W, Erdi 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. Berlin: Springer . 2012. p. 427-434. (Lecture notes in computer science). Available from, DOI: 10.1007/978-3-642-33266-1_53

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title = "Neural networks for proof-pattern recognition",

author = "Ekaterina Komendantskaya and Kacper Lichota",

year = "2012",

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

isbn = "9783642332654",

series = "Lecture notes in computer science",

publisher = "Springer",

pages = "427--434",

editor = "Villa, {Alessandro E. P. } and Wlodzislaw Duch and Peter Erdi and Francesco Masulli and Gunther Palm",

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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. © 2012 Springer-Verlag.

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. © 2012 Springer-Verlag.

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

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

M3 - Conference contribution

SN - 9783642332654

T3 - Lecture notes in computer science

SP - 427

EP - 434

BT - Artificial Neural Networks and Machine Learning – ICANN 2012

PB - Springer

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