关键词:

扎根理论, 在线论坛, 属性抽取, 文本挖掘, 归纳法

Abstract:

Perceived quality is the consumer’s perceptual knowledge of product attributes, which is very important to manufacturers. Considering that the product attributes perceived by consumers are different from the attribute system in enterprise production, a perceived quality attribute extraction method based on the grounded theory is constructed for online forum data. The method consists of two phases, i.e., extracting rules by inductive method process in the coding process to better adapt to the big data context, and proposing a three-stage testing process based on the text mining method in the theory saturation test to reduce the manual workload. Eight consumer-perceived car attributes are obtained in the instance analysis of a large amount of car forum data. The method ensures the completeness of attribute extraction and reduces the manual workload. This paper has theoretical significance for the research on perceived quality and attribute extraction, and improves the big data processing capability of manufacturers.

Key words:

grounded theory, online forums, attribute extraction, text mining, inductive methods