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Home > Archive>Volume 29, Issue 7, 2018 >2046-2070. DOI:10.13328/j.cnki.jos.005538
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Features Oriented Survey of State-of-the-Art Keyphrase Extraction Algorithms
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National Natural Science Foundation of China (U1533104, U1633110, 61603028); Fundamental Research Funds for the Central Universities (ZXH2012P009)

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    Abstract:

    Keyphrases that efficiently represent the main topics discussed in a document are widely used in various document processing tasks, and automatic keyphrase extraction has been one of fundamental problems and hot research issues in the field of natural language processing (NLP). Although automatic keyphrase extraction has received a lot of attention and the extraction technologies have developed quickly, the state-of-the-art performance on this task is far from satisfactory. In order to help to solve the keyphrase extraction problem, this paper presents a survey of the latest development in keyphrase extraction, mainly including candidate keyphrase generation, feature engineering and keyphrase extraction models. In addition, some published datasets are listed, the evaluation approaches are analyzed, and the challenges and trends of automatic keyword extraction techniques are also discussed. Different from the existing surveys that mainly focus on the models of keyphrase extraction, this paper provides a features oriented survey of automatic keyphrase extraction. This perspective may help to utilize the existing features and propose the new effective extraction approaches.

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常耀成,张宇翔,王红,万怀宇,肖春景.特征驱动的关键词提取算法综述.软件学报,2018,29(7):2046-2070

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  • Received:July 19,2017
  • Revised:November 02,2017
  • Online: February 08,2018
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