Fuzzy model-based analysis of user feedback for product development insights
The topic of this paper belongs to the modeling of human-software experience to support product development. The primary objective of this paper is to present a structured modeling framework, incorporating user feedback to support software product development. The proposed modeling framework constru...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025019231 |
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| Summary: | The topic of this paper belongs to the modeling of human-software experience to support product development. The primary objective of this paper is to present a structured modeling framework, incorporating user feedback to support software product development. The proposed modeling framework constructs a model that outlines the relationship between measurable parameters of objective and subjective user feedback and the evaluation metrics of software and user capability, motivated by the typical disparity between feedback parameters and capability metrics. A key benefit of the framework is its visually enhanced interpretability power. The resulting model is based on a manageable set of linguistic fuzzy rules, designed to remain at a level comprehensible to human intuition, thereby enabling developers to understand the primary causal relationships. A further benefit of the framework is its adaptability across the entire application lifecycle; it can initiate with minimal user feedback and is computationally equipped to handle the gradually increasing volume of feedback over time. Thus, this approach serves two critical purposes: first, to guide the development team in identifying features that require enhancement to better align with user needs; and second, to optimize the alignment between the application's functionalities and the diverse capabilities of its user base. Beyond this proposed framework, the primary novelty in the field of modeling lies in the special modification of the TS fuzzy model transformation method that enables the selection of principal components within the fuzzy rules and facilitates the use of interpretable fuzzy sets, along with a pseudo-inverse-based model adaptation that mitigates the computational load as the number of users grows. The effectiveness of the proposed framework is demonstrated through four use case examples. The first use case is in a hypothetical example for illustrative purposes to intuitively clarify the framework's functionality. The second models user demographics, digital content engagement, and VR platform adaptation preferences. The third addresses the subjective and objective challenges of users when performing tasks in 2D versus 3D environments. The fourth examines the experience of spatial presence in 3D environments. |
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| ISSN: | 2405-8440 |