Abstract
A method for developing a structural model of natural language syntax and semantics is proposed. Syntactic and semantic relations between parts of a sentence are presented in the form of a recursive structure called a control space. Numerical characteristics of these data are stored in multidimensional arrays. After factorization, the arrays serve as the basis for the development of procedures for analyses of natural language semantics and syntax.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Van de Cruys, T.: A Non-negative Tensor Factorization Model for Selectional Preference Induction. Journal of Natural Language Engineering 16(4), 417–437 (2010)
Van de Cruys, T., Rimell, L., Poibeau, T., Korhonen, A.: Multi-way Tensor Factorization for Unsupervised Lexical Acquisition. In: Proceedings of COLING 2012, pp. 2703–2720 (2012)
Cohen, S.B., Collins, M.: Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs. In: NIPS 2012, pp. 2528–2536 (2012)
Wei, P., Tao, L.: On the equivalence between nonnegative tensor factorization and tensorial probabilistic latent semantic analysis. Applied Intelligence, Springer Journals 35(2), 285–295 (2011)
Anisimov, A.V.: Control space of syntactic structures of natural language. Cybernetics and System Analysis 93, 11–17 (1990)
Chomsky, N.: Syntactic Structures, 117 p. Mouton & Co. (1957)
Tesnière, L.: Èlèments de syntaxe structurale. Klincksieck, Paris (1959)
Klein, D., Manning, C.D.: Accurate Unlexicalized Parsing. In: Proceedings of ACL 2003, pp. 423–430 (2003)
de Marneffe, M.-C., MacCartney, B., Manning, C.D.: Generating Typed Dependency Parses from Phrase Structure Parses. In: Proceedings of LREC (2006), http://nlp.stanford.edu/pubs/LREC06_dependencies.pdf
Lee, D.D., Seung, H.S.: Algorithms for Non-Negative Matrix Factorization. In: NIPS (2000), http://hebb.mit.edu/people/seung/papers/nmfconverge.pdf
Cichocki, A., Zdunek, R., Phan, A.-H., Amari, S.-I.: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation. J. Wiley & Sons, Chichester (2009)
Kasami, T.: An efficient recognition and syntax-analysis algorithm for context-free languages. Scientific report AFCRL-65-758. Air Force Cambridge Research Lab, Bedford, MA (1965)
Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science 41(6), 391–407 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Anisimov, A., Marchenko, O., Taranukha, V., Vozniuk, T. (2014). Development of a Semantic and Syntactic Model of Natural Language by Means of Non-negative Matrix and Tensor Factorization. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science(), vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-10816-2_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10815-5
Online ISBN: 978-3-319-10816-2
eBook Packages: Computer ScienceComputer Science (R0)