计算机科学 ›› 2023, Vol. 50 ›› Issue (12): 294-301.doi: 10.11896/jsjkx.221000083
臧洁, 周万林, 王妍
ZANG Jie, ZHOU Wanlin, WANG Yan
摘要： 考虑企业资源与客户需求匹配问题,现有的方法存在资源和需求封装不够准确以及匹配效果无法满足用户需求等问题。为解决企业资源与需求描述的多样性和歧义性,提出了动态自定义模板封装。针对封装后的需求与资源大多都是中文短文本这一特点,兼顾句子间语义的差异性和相似性,提出了融合多头注意力机制和孪生网络的交互型文本匹配模型。模型使用字词混向量作为输入增强文本的语义信息,将孪生网络与多头注意力机制相融合,作为独立单元提取上下文的语义特征并使语义特征充分交互。为了验证模型的有效性,在经典数据集LCQMC和自我构建的CSMD数据集上对模型进行了实验,结果表明所提模型在准确率和性能等方面均有不同程度的提升,为企业资源与需求提供了更精准的匹配方法。
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