大数据环境下基于SOM神经网络的竞争对手识别方法研究

Research on Competitor Identification Method Based on SOM Neural Network in Big Data Environment

[目的/意义]大数据环境下,传统的竞争对手识别方法存在局限性,文章针对这种不足提出了一种能够适应大数据环境的竞争对手识别方法。[方法/过程]第一,基于互联网下顾客价值领先战略,从消费者角度出发,选择基于消费者情感特征的竞争对手评价体系;第二,以顾客评论作为数据源,通过对评论文本分析,提取顾客关注的产品特征;第三,基于文本情感分析技术计算企业相应产品特征的顾客情感得分;第四,基于自组织神经网络(SOM)构建竞争对手识别模型,并根据模型结果识别目标企业竞争对手。[结果/结论]使用酒店行业顾客评论数据进行实验,证实了该方法能够在大数据环境下快速、高效、客观地识别企业竞争对手。

[Purpose/significance]In the big data environment,the traditional competitor identification methods have limitations.This article proposes a competitor identification method that can adapt to the big data environment in response to this deficiency.[Method/process]Firstly,based on the customer value leadership strategy under the internet,from the perspective of consumers,choose a competitor evaluation system based on consumer emotional characteristics.Secondly,use customer reviews as the data source and analyze the text of reviews.Extract the product features that customers pay attention to.Thirdly,calculate the customer sentiment score of the company’s corresponding product features based on text sentiment analysis technology.Fourthly,build a competitor identification model based on self-organizing neural network(SOM),and identify the target company’s competition based on the model results opponent.[Result/conclusion]Experiments using customer review data in the hotel industry proved that this method can quickly,efficiently and objectively identify corporate competitors in the big data environment.