Research on the weak demand signal identification model of innovative product based on domain ontology construction

Abstract

PurposeThis paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.Design/methodology/approachTo address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.FindingsEmpirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.Originality/valueThis paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

A Semantic Retrieval Algorithm for Enterprise Archives Based on Bert-BiGRU-CRF-Harris Hawk Model

“…For technological exploration and innovation, To adapt the complex structure and strong attribute diversity of transportation infrastructure, Tuyu Bao, Kun Chen 22 et al established an ontology-based semantic similarity calculation model is constructed with three approaches, including Edge-Counting method, Feature-based method, and Information-Content method. Dongyuan Zhao, Zhongjun Tang, Fengxia Sun 23 proposed a domain ontology approach to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identi cation. The framework provides a basis for identifying such signals and introduces evaluation indices.…”

“…The F-measure comprehensive evaluation index is based on accuracy and recall rate. These metrics are calculated by (20) to (23) are as follows:…”