Grammar and Lexical Functional Text Categorization & Clustering in NLM

DaffyDoc (United States of America)
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Full list of words from this list:

words only definitions & notes
  1. phrase structure
    the grammatical arrangement of words in sentences
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  2. probabilistic
    of or relating to or based on probability
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  3. indigenous language
    a language that originated in a specified place and was not brought to that place from elsewhere
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  4. electronic dictionary
    a machine-readable version of a standard dictionary
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  5. natural language processing
    the branch of information science that deals with natural language information
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  6. typology
    classification according to general category or kind
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  7. lexical
    of or relating to words
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  8. ARDA
    an agency of the Intelligence Community that conducts advanced research and development related to information technology
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  9. categorization
    the basic cognitive process of arranging into classes
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  10. DARPA
    the central research and development organization for the United States Department of Defense; responsible for developing new surveillance technologies since 9/11
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  11. usability
    the quality of being able to provide good service
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  12. natural language
    a human written or spoken language used by a community
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  13. syntactic
    of or relating to or conforming to the rules of syntax
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  14. lexicography
    the act of writing, editing, and examining dictionaries
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  15. linguistically
    with respect to language
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  16. NSF
    an independent agency of the federal government responsible for the promotion of progress in science and engineering by supporting programs in research and education
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  17. sophisticate
    a person who is cultured and has worldly experience
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  18. parse
    analyze the sentence structure of
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  19. computational
    of or involving calculation
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  20. textual
    relating to or based on writing
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  21. gib
    a castrated tomcat
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  22. extraction
    taking out something
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  23. grammar
    the branch of linguistics that deals with sentence structure
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  24. statistical
    of or relating to the interpretation of quantitative data
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  25. induction
    the act of bringing about something
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  26. constraint
    the state of being physically limited
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  27. processing
    preparing or putting through a prescribed procedure
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  28. linguistic
    consisting of or related to language
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  29. clustering
    a grouping of a number of similar things
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  30. incorporate
    make into a whole or make part of a whole
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  31. Stanford
    a university in California
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  32. functional
    designed for or capable of a particular use
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  33. intelligently
    in an intelligent manner
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  34. robust
    sturdy and strong in form, constitution, or construction
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  35. indigenous
    originating where it is found
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  36. sophisticated
    having worldly knowledge and refinement
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  37. model
    a representation of something, often on a smaller scale
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  38. cluster
    a grouping of a number of similar things
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  39. focus on
    center upon
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  40. fellowship
    the state of being with someone
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  41. research
    a seeking for knowledge
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  42. partnership
    a cooperative relationship between people or groups
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  43. funding
    financial resources provided to make some project possible
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  44. electronic
    relating to or operating by a controlled current
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  45. dictionary
    a reference book containing an alphabetical list of words
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  46. language
    a means of communicating by the use of sounds or symbols
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  47. award
    give, especially as an honor
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  48. topic
    the subject matter of a conversation or discussion
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  49. include
    have as a part; be made up out of
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  50. domain
    a particular environment or walk of life
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  51. base
    lowest support of a structure
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  52. presentation
    the act of formally giving something, as a prize
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  53. currently
    at this time or period
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  54. process
    a particular course of action intended to achieve a result
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  55. Christopher
    Christian martyr and patron saint of travellers
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  56. mining
    the act of extracting ores or coal from the earth
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  57. Scottish
    of or relating to or characteristic of Scotland or its people or culture or its English dialect or Gaelic language
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  58. Australian
    of or relating to or characteristic of Australia or its inhabitants or its languages
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  59. text
    the words of something written
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  60. faculty
    an inherent cognitive or perceptual power of the mind
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  61. based
    having a base
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  62. focus
    the concentration of attention or energy on something
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  63. work on
    to exert effort in order to do, make, or perform something
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  64. theory
    a belief that can guide behavior
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  65. phrase
    an expression consisting of one or more words
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  66. particularly
    to a distinctly greater extent or degree than is common
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  67. enterprise
    a purposeful or industrious undertaking
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  68. fund
    a reserve of money set aside for some purpose
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  69. structure
    a complex entity made of many parts
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  70. supported
    held up or having the weight borne especially from below
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  71. information
    knowledge acquired through study or experience
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  72. driven
    compelled forcibly by an outside agency
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  73. natural
    relating to or concerning the physical world
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  74. produce
    bring forth or yield
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  75. previous
    just preceding something else in time or order
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  76. drive
    operate or control a vehicle
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  77. current
    occurring in or belonging to the present time
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  78. council
    a body serving in an administrative capacity
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  79. opportunity
    a possibility from a favorable combination of circumstances
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  80. particular
    unique or specific to a person or thing or category
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  81. support
    the act of bearing the weight of or strengthening
    My research at Stanford is currently supported by an IBM Faculty Partnership Award, ARDA, Scottish Enterprise, and DARPA.
  82. rich
    possessing material wealth
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  83. works
    performance of moral or religious acts
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  84. mine
    excavation from which ores and minerals are extracted
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  85. system
    a group of independent elements comprising a unified whole
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  86. interest
    a sense of concern with and curiosity about something
    Particular research interests include probabilistic models of language, statistical natural language processing, information extraction, text mining, robust textual infererence, statistical parsing, grammar induction, constraint-based theories of grammar, and computational lexicography.
  87. real
    being or occurring in fact or actuality
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  88. human
    a person; a hominid with a large brain and articulate speech
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  89. man
    an adult person who is male (as opposed to a woman)
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  90. use
    put into service
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  91. head
    the upper part of the human body or the body in animals
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
  92. work
    activity directed toward making or doing something
    Christopher D. Manning Manning works on systems that can intelligently process and produce human languages.
  93. world
    the 3rd planet from the sun; the planet we live on
    My current research focuses on robust but linguistically sophisticated probabilistic natural language processing, and opportunities to use it in real-world domains.
  94. come
    move toward, travel toward
    Previous funding at Stanford comes from a Terman Fellowship, NSF (for GIB), NTT, NHK, and the Australian Reseach Council.
  95. such
    of so extreme a degree or extent
    Particularly topics include richer models for probabilistic parsing, grammar induction, text categorization and clustering, incorporating probabilistic models into constraint-based syntactic theories such as Head-driven Phrase Structure Grammar and Lexical Functional Grammar, electronic dictionaries and their usability, particularly for indigenous languages, information extraction and presentation, and linguistic typology.
Created on Mon Aug 26 01:17:22 EDT 2013

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