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Automatically Quantifying Customer Need Tweets: Towards a Supervised Machine Learning Approach

机译:自动量化客户需求推文:采用有监督的机器学习方法

摘要

The elicitation of customer needs is an important task for businesses in order to design customer-centric products and services. While there are different approaches available, most lack automation, scalability and monitoring capabilities. In this work, we demonstrate the feasibility to automatically identify and quantify customer needs by training and evaluating on previously-labeled Twitter data. To achieve that, we utilize a supervised machine learning approach. Our results show that the classification performances are statistically superior-”but can be further improved in the future.
机译:激发客户需求是企业设计以客户为中心的产品和服务的重要任务。尽管有不同的方法可用,但大多数方法都缺乏自动化,可伸缩性和监视功能。在这项工作中,我们演示了通过培训和评估先前标记的Twitter数据来自动识别和量化客户需求的可行性。为了实现这一目标,我们采用了监督式机器学习方法。我们的结果表明,分类性能在统计上优于“”,但将来可以进一步提高。

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