Extracting Customer-Related Information for Need Identification
Extracting Customer-Related Information for Need Identification
复制标题
提取客户相关信息以进行需求识别
DOI：
10.1007/978-3-030-02053-8_169
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
R. Schmitt
中科院分区：
文献类型：
--
作者：
A. Fels;K. Briele;M. Ellerich;R. Schmitt
在社交媒体上发布的关于产品或服务的客户生成内容越来越多，这是公司的重要信息来源。特别是对于产品开发项目或服务报价的设计，以所谓的产品评论形式表达的公正反馈是最有价值的。然而，为了有效利用产品评审内容，开发自动化文本处理工具是必不可少的；手动文本处理方法非常耗时，因此会损害提取信息提供的好处。到目前为止，自动文本挖掘工具专注于分析产品评论中所表达的客户偏好和情感。对客户相关内容的自动提取和分析尚未进行详细研究。顾客相关内容是指评审中的信息，这些信息主要与产品无关，而是提供有关顾客本人、其使用行为、个人环境和习惯的信息。这些信息通常由作者（即客户）以客观的方式表达，并为识别客户需求提供了一个真实的起点。特别是在创新产品开发中，考虑客户习惯和个人环境与潜在需求的推导高度相关，这可能比了解关于产品的特定偏好更重要。本研究的目的是开发和验证从产品评论中提取客观内容的文本挖掘过程。为此，我们收集了来自Amazon.de的两类产品的德语评论，并首先手工标注以供验证参考。在此基础上，提出了一个包含文本准备、转换、分类和性能评价的文本挖掘过程。应用了三种不同的分类器进行性能比较。
The increasing amounts of customer-generated content regarding a product or service published in Social Media are an important source of information for companies. Especially for product development projects or the design of service offers, the unbiased feedback expressed in so-called product reviews is most valuable. However, for the effective use of product review content, the development of automated text processing tools is essential; manual text processing approaches are very time-consuming and thus compromise the benefits provided from the extracted information. To date, automated text mining tools focus the analysis of customers preferences and emotions articulated within a product review. An automated extraction and analysis of customer-related content has not yet been investigated in detail. Customer-related content refers to information within a review, which does not primarily concern the product, but provide information about the customer himself, his usage behavior, personal environment and habits. This information is most generally expressed in an objective manner by the author (i.e. customer) and provides an authentic starting point for the identification of customer needs. Particularly for innovative product development, the consideration of customer habits and personal environment is highly relevant for the derivation of underlying needs, which can be more important than the knowledge of specific preferences regarding a product. The objective of this research is the development and validation of a text mining process for the extraction of objective content from product reviews. To this end, German reviews from Amazon.de regarding two product categories are collected and firstly annotated manually for validation reference. Thereafter, a text mining process is developed comprising text preparation, transformation, classification and performance evaluation. Three different classifiers are applied for performance comparison.
登录
查看更多内容
识别隐藏的需求
影响因子：
4.2
作者：
K. Goffin;F. Lemke;U. Koners
通讯作者：
U. Koners
在线消费者评论中的互文性和互话语性
影响因子：
4.2
作者：
Camilla Vásquez
通讯作者：
Camilla Vásquez
SentiStorm：Tweets 的 Echtzeit-Stimmungserkennung
DOI：
10.1365/s40702-016-0237-6
发表时间：
2016
期刊：
HMD Praxis der Wirtschaftsinformatik
影响因子：
--
作者：
Eva Zangerle;Martin Illecker;G. Specht
通讯作者：
G. Specht
新产品开发中的客户整合——关于不同客户整合方法获取客户知识的适当性的文献综述
影响因子：
10.5
作者：
Shkodran Zogaj;U. Bretschneider
通讯作者：
U. Bretschneider