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    ARTICLE

    TdBrnn: An Approach to Learning Users’ Intention to Legal Consultation with Normalized Tensor Decomposition and Bi-LSTM

    Xiaoding Guo1, Hongli Zhang1, *, Lin Ye1, Shang Li1

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 315-336, 2020, DOI:10.32604/cmc.2020.07506

    Abstract With the development of Internet technology and the enhancement of people’s concept of the rule of law, online legal consultation has become an important means for the general public to conduct legal consultation. However, different people have different language expressions and legal professional backgrounds. This phenomenon may lead to the phenomenon of different descriptions of the same legal consultation. How to accurately understand the true intentions behind different users’ legal consulting statements is an important issue that needs to be solved urgently in the field of legal consulting services. Traditional intent understanding algorithms rely heavily on the lexical and semantic… More >

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