基于数据驱动的用户需求智能获取方法研究

Intelligent Acquisition Method of User Requirements Based on Data Driven

目的数字化浪潮下人们的消费行为也发生了改变。线上购物伴生着大量用户评论,具有实时、真实、全面等特点,这是挖掘用户需求的绝佳资料。本文利用线上评论,结合感性工学和自然语言处理技术,提取其中对应于产品元素的用户需求,为后来的产品改进或开发提供指导。方法本文通过爬虫工具获取目标产品大量评论,对文本进行词频分析筛选出要分析的产品元素,根据筛选结果将评论归类,从中提取形容词汇,并经过专家汇总,最后对含有形容词的语句进行情感分析,获取用户对产品的需求信息。最后依靠感性工学指导后续设计方案生成。结论本文用亚马逊网站上山地自行车产品进行实例验证,结果证明该方法能够快速高效地获得用户对产品的准确评价,是一种切实可行的获取用户需求的智能化设计方法。

Under the digital wave,people's consumption behavior has also changed.Online shopping is accompanied by a large number of user reviews,which are real-time,true,and comprehensive.This is an excellent data for mining user needs.This research uses online reviews,combined with Kansei engineering and natural language processing technology,to extract user needs corresponding to product elements,and provide guidance for subsequent product improvement or development.This article first obtains a large number of reviews of the target product through a crawler tool,performs word frequency analysis on the text to filter out the product elements to be analyzed,and then categorizes the reviews according to the screening results,extracts adjectives from them,and summarizes them by experts,and then conducts the sentence containing adjectives Sentiment analysis to obtain information about the needs of users for the product.Finally,rely on Kansei engineering to guide the generation of subsequent design schemes.This paper uses the mountain bike product on Amazon website to verify the actual situation,and the result proves that this method can quickly and efficiently obtain the user's accurate evaluation of the product,and it is a practical and feasible intelligent design method to obtain the user's needs.