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Home > Art, Film & Photography > Tasks of Natural Language Processing: Word Sense Disambiguation, Lexicography, Machine Translation, Automatic Summarization
Tasks of Natural Language Processing: Word Sense Disambiguation, Lexicography, Machine Translation, Automatic Summarization

Tasks of Natural Language Processing: Word Sense Disambiguation, Lexicography, Machine Translation, Automatic Summarization


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About the Book

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 28. Chapters: Word sense disambiguation, Lexicography, Machine translation, Automatic summarization, Part-of-speech tagging, Automatic Acquisition of Sense-Tagged Corpora, Anaphora, Terminology extraction, Asia Online, Named entity recognition, Lesk algorithm, Text segmentation, Language identification, Yarowsky algorithm, Word sense induction, Sentence boundary disambiguation, Lemmatisation, Relationship extraction, Linguistic empathy, Lexical substitution, Bootstrapping, Tokenization, Collocation extraction, Truecasing, Shallow parsing, Semantic role labeling, Phrase chunking. Excerpt: In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings (polysemy). The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference and others. Research has progressed steadily to the point where WSD systems achieve sufficiently high levels of accuracy on a variety of word types and ambiguities. A rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date. Current accuracy is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs ach...


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Product Details
  • ISBN-13: 9781155646435
  • Publisher: Books LLC, Wiki Series
  • Publisher Imprint: Books LLC, Wiki Series
  • Height: 246 mm
  • No of Pages: 30
  • Spine Width: 2 mm
  • Weight: 73 gr
  • ISBN-10: 1155646436
  • Publisher Date: 26 Jul 2011
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Word Sense Disambiguation, Lexicography, Machine Translation, Automatic Summarization
  • Width: 189 mm


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