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File: Processing Pdf 180914 | Naturallanguageprocessing
natural language processing matilde marcolli cs101 mathematical and computational linguistics winter 2015 cs101 win2015 linguistics natural language processing reference c d manning h schutze foundations of statistical natural language processing ...

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                                 Natural Language Processing
                                                 Matilde Marcolli
                     CS101: Mathematical and Computational Linguistics
                                                    Winter 2015
                                 CS101 Win2015: Linguistics      Natural Language Processing
          Reference
                 C.D. Manning, H. Schutze,¨                  Foundations of Statistical Natural
                 Language Processing, MIT Press, 1999.
                                 CS101 Win2015: Linguistics      Natural Language Processing
          • Setting based on Probabilistic Linguistics
          • Electronic Corpora
          - Linguistic Data Consortium
          - European Language Resources Association
          - International Computer Archive of Modern English
          - Oxford Text Archive
          - Child Language Data Exchange System
          • Stemming: stripping off affixes and word formation and extract
          stem of words from a word list
          • Markup: syntactic structure is marked
          • Penn Treebank: Lisp-like bracketing to mark binary tree
          structure of sentence
          • SGML (Standard Generalized Markup Language): HTML is a
          type of SGML encoding; Text Encoding Initiative (TEI) encoding
          scheme suitable for marking parts of various texts, XML simplified
          form good for web applications
                                 CS101 Win2015: Linguistics      Natural Language Processing
          • Grammatical Tagging: automated tagging for categories (parts
          of speech: nouns, verbs,...)
          • Tag Sets: American Brown Corpus (developed to tag the
          Lancaster–Oslo–Bergen corpus and British National Corpus)
          • Penn Treebank tag set: most widely used in computational
          setting (simplified version of previous)
          • rule: least marked category is used as default whenever a word
          cannot be placed in any other more precise subcategory with
          additional markings
          • Example: “Adjectives” used if cannot further place into
          “comparatives, superlatives, numerals,...”
          • available tag sets are very different (some coarser, some more
          refined)
                                 CS101 Win2015: Linguistics      Natural Language Processing
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...Natural language processing matilde marcolli cs mathematical and computational linguistics winter win reference c d manning h schutze foundations of statistical mit press setting based on probabilistic electronic corpora linguistic data consortium european resources association international computer archive modern english oxford text child exchange system stemming stripping o axes word formation extract stem words from a list markup syntactic structure is marked penn treebank lisp like bracketing to mark binary tree sentence sgml standard generalized html type encoding initiative tei scheme suitable for marking parts various texts xml simplied form good web applications grammatical tagging automated categories speech nouns verbs tag sets american brown corpus developed the lancaster oslo bergen british national set most widely used in version previous rule least category as default whenever cannot be placed any other more precise subcategory with additional markings example adjectives...

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