Survey on Automatic Term Extraction Research
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National Natural Science Foundation of China (61772537, 61772536, 61702522, 61532021); National Key Research and Development Program of China (2018YFB1004401)

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    Abstract:

    Automatic term extraction is to extract domain-related words or phrases from document collections. It is a core basic problem and research hotspot in the fields of ontology construction, text summarization, and knowledge graph. In particular, under the rise of unstructured text studies in big data, automatic term extraction technology has been further concerned by researchers and has obtained rich research results recently. With the terminology sorting algorithm as the main clue, this study surveys the basic theories, technologies, current research works, advantages and disadvantages of automatic term extraction methods. First, the formalized definition and solution framework of automatic term extraction problem are outlined. Then, based on the features of the basic language information and the relational structure information in the "shallow parsing", the latest study results are classified, research progress and major challenges of existing automatic term extraction methods are summarized systematically. Finally, some available data resources are listed, evaluation approaches are analyzed, and the possible research trends in the future are predicted.

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张雪,孙宏宇,辛东兴,李翠平,陈红.自动术语抽取研究综述.软件学报,2020,31(7):2062-2094

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History
  • Received:September 17,2019
  • Revised:February 09,2020
  • Adopted:
  • Online: April 21,2020
  • Published: July 06,2020
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