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31. Natural language retrieval is the trend of information retrieval.

32. Statements are analogous to sentences in a natural language.

33. Natural Language Generation(NLG) is the subfield of artificial intelligence and computational linguistics that(focuses) on computer system that can produce understandable texts.

34. Therefore, any reasonably designed XML document should reflect certain semantic structure isomorphous to human conceptual structure, and hence expressible by human natural language.

35. Therefore, the representation and acquisition of knowledge play a key information processing and natural language understanding.

36. Finally, introduced the process that the natural language understanding theory applies in the product - design.

37. Coreference resolution plays an important role in natural language processing.

38. Forgive me if I stumble through my explanations of the quite remarkable Natural Language Toolkit (NLTK), a wonderful tool for teaching, and working in, computational linguistics using Python.

38. Sentencedict.com try its best to collect and create good sentences.

39. A natural language sentence can be transformed into a word tag string or a sentence pattern.

40. File Change Semantics is a formal semantic theory that dynamically describes the meaning of natural language that is developed from the traditional Montague's formal semantics.

41. By the NLIDB, the user input the query of natural language. And how to auto-identify in computer is the key technology of the natural language interface.

42. Touch, voice, natural language input, Smart Phones, Smart PC's, Smart TV's.

43. The central theme is that the analysis of semantic paradigm and syntagm of verbs, the bottleneck in NLP, form the groundwork in natural language information processing.

44. Anaphora resolution is a key step in Natural Language Processing (NLP) and a kernel task in many language engineering applications.

45. This paper introduced a knowledge representation model for multilingual natural language text generation system.

46. The natural language essentially is a self meta-language, therefore, traditionally it always is compilation tool in the dictionary.

47. Using NLU technology in the database query system and designing NLQID(natural language query interface of database) has become one of the most hopeful applied fields in the research on NLU.

48. Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text.

49. Firstly, The production of this research will provide a study foundation for natural language information operation.

50. Automatic summarization is an important issue in natural language processing.

51. IP addresses can be represented by a natural language convention called domain names.

52. The innovative solution has been already applied to the natural language intelligent network Question Answering system. The application achieved well results.

53. Mining geo-spatial information from natural language not only enriches information sources for Geographic Information System (GIS) but also enhances representability and perceptibility of GIS.

54. This paper presents an approach to the automatic enrichment of lexicon in a natural language understanding system to simulate man's word learning ability.

55. The automatic transcription, annotation and retrieval of broadcasting news requires automatic speech recognition,(sentencedict.com) natural language processing and information retrieval technologies.

56. Two combinable nucleus sentences can be joined to make a expansible sentence. Such expansion in natural language has its own Characteristics:twofold, threefold or even multifold.

57. Maximum entropy model provides a natural language processing method, and proposes a structured program of medical text information combined with standard terminology for health care.

58. Because of the speciality of natural language retrieval (NLR) and the affection of synonym and polysemy in tradition information retrieval model, the precision of retrieval is not high.

59. Maximum Entropy Models for Natural Language Ambiguity Resolution . Ph . D . Dissertation . University of Pennsylvania, pp .6 - 18.

60. Open domain question answering (QA) represents a challenge of natural language processing, aiming at returning exact answers in response to natural language questions.