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Multi-Level Knowledge Engineering Approach for Mapping Implicit Aspects to Explicit Aspects

Computers, Materials & Continua 2022年第2期70卷 3491-3509页

作者： Jibran Mir Azhar Mahmood Shaheen Khatoon Computer Science Department Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(SZABIST)Faculty of Computing and Engineering SciencesIslamabadPakistan Department of Computer Science Capital University of Science&TechnologyFaculty of ComputingIslamabad College of Computer Science and Information Technology King Faisal UniversitySaudi Arabia

Aspect’s extraction is a critical task in aspect-based sentiment analysis,including explicit and implicit aspects *** extensive research has identified explicit aspects,little effort has been put forward on implicit aspects extraction due to the complexity of the ***,existing research on implicit aspect identification is widely carried out on product reviews targeting specific aspects while neglecting sentences’dependency ***,in this paper,a multi-level knowledge engineering approach for identifying implicit movie aspects is *** proposed method first identifies explicit aspects using a variant of bilstm and CRF(Bidirectional Long Short Memory-Conditional Random Field),which serve as a memory to process dependent sentences to infer implicit *** can identify implicit aspects from four types of sentences,including independent and three types of dependent *** study is evaluated on a largemovie reviews dataset with 50k *** experimental results showed that the explicit aspect identification method achieved 89%F1-score and implicit aspect extraction methods achieved 76%*** addition,the proposed approach also performs better than the state-of-the-art techniques(NMFIAD andML-KB+)on the product review dataset,where it achieved 93%precision,92%recall,and 93%F1-score.

关键词： Movie NEs(named entities) aspects opinion words annotation process memory implicit aspects implicit aspects mapping word embedding and bilstm

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