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2021 , Vol. 65 >Issue 8: 85 - 96

DOI: https://doi.org/10.13266/j.issn.0252-3116.2021.08.009

KNOWLEDGE ORGANIZATION

Integrating Word Semantic Representation and New Word Identification for Domain Ontology Evolution: A Case Study of Product Online Reviews

  • Geng Qian ,
  • Deng Siyu ,
  • Jin Jian
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  • 1 Center for Governance Studies, Beijing Normal University, Zhuhai 519087;
    2 School of Government, Beijing Normal University, Beijing 100875

Received date: 2020-10-15

  Revised date: 2021-01-12

  Online published: 2021-06-02

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Abstract

[Purpose/significance] Due to the inaccuracy and low efficiency in capturing new knowledge and new requirements in traditional ontology evolution, based on domain new word identification, an ontology evolution method is proposed and evaluated by analyzing a large volume of product online reviews.[Method/process] First, a series of natural language processing algorithms were used to pre-process product review text corpus, and the Word2vec algorithm was adopted for word vector embedding. Then, a Bi-LSTM-Attention-CRF algorithm was utilized for the recognition and extraction of new words in a candidate set, and the K-means algorithm was applied for clustering to get the final domain new words. Finally, the Six-Stage evolution process of ontology evolution was invited for analyzing domain ontology evolution.[Result/conclusion] By analyzing smart phone reviews as examples, it can be found that the proposed approach about new word identification presents a higher accuracy and recall rate and a new version of the product ontology in the smart phone domain can be evolved accordingly. It helps designers to optimize feature and function configuration in new product development and consumers to analyze online opinions for purchase decisions.

Key words： ontology evolution; domain new words; new word detection; attention mechanism; Bi-directional Long Short-Term-Memory; Conditional Random Field

Cite this article

Geng Qian , Deng Siyu , Jin Jian . Integrating Word Semantic Representation and New Word Identification for Domain Ontology Evolution: A Case Study of Product Online Reviews[J]. Library and Information Service, 2021 , 65(8) : 85 -96 . DOI: 10.13266/j.issn.0252-3116.2021.08.009

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