I have recently started learning Natural Language Processing and while reading research papers I came across terms like "Latent Dirichlet Allocation", "Latent Semantic Analysis", "Gaussian Distribution", etc. and I am unable to understand these topics from Wikipedia and other sources. So can you suggest me some good books for the same, i.e. semantic analysis in NLP?
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Do you mean semantic analasys from a theoretical or from a computational point of view? Because the terms you mentioned sound a lot like you are primarily interested in computer-driven analysis and wouldn't be very happy with a standard textbook for linguists.– Natalie ClariusJul 26, 2016 at 18:58
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Yes, I am more interested from computational point of view.– Riken ShahJul 26, 2016 at 19:04
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1Okay. I'm sorry I can not make many recommendations there; in case you also want to consult introductions to semantics as done in general linguistics (you should have some basic knowledge in order to be able to approach it from an NLP side), some recommendations can be found here.– Natalie ClariusJul 26, 2016 at 19:40
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1@Reviewers Whether or not this question is too broad probably depends on whether there is a comprehensive textbook that covers all (or most) of what the OP mentioned. I would think there are at least some introductory ones and the recommendations might be interesting to other people too, so I'd leave this question open.– Natalie ClariusJul 27, 2016 at 10:44
2 Answers
Here are some. Hope that helps.
1) Hobbs, J. R. and Shieber, S. M. (1987). An algorithm for generating quantifier scopings. Computational Linguistics,13(1), 47–55.
2) Main, M.G. and Benson, D. B. (1983). Denotational semantics for natural language question-answering programs. American Journal of Computational Linguistics, 9(1), 11-21.
3) Simmons, R. F. (1983). Computations from the English. Prentice Hall.
4) Schubert, L. K. and Pelletier, F. J. (1982). From English to logic: Context-free computation of ‘conventional’ logical translation. American Journal of Computational Linguistics, 8(1), 27–44.
Checkout the ACL their papers are (nearly?) all available online. Use Google Scholar to figure out which are the important ones ;)