ArticleComputational intelligence and neuroscience2022
Design Model of Cultural and Creative Products Using User Perception Demand Mining.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 7 citations in OpenAlex.
- Retracted: Design Model of Cultural and Creative Products Using User Perception Demand Mining.Computational intelligence and neuroscience · 2023Article
Corrections and comments
- Retraction · 2023-07-12Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People are becoming more and more aware of the value of design throughout a product's entire life cycle as a result of the fierce competition for industrial products that exists today. The life of a product involves its design, manufacture, sale, and use, and how well these links are managed determines the product's positioning in terms of value in the eyes of consumers. The key to the functional integration of the design is monitoring the entire process and applying the user's emotional needs. A useful tool for assessing users' emotional needs is the perceptual image of a product. An artificial intelligence-driven method for product perceptual design is proposed, and its efficacy is demonstrated by the design of an optometer. This method addresses the issues of incomplete measurement and insufficient sample collection in the traditional users' perceptual cognition measurement. The findings demonstrate that extracting users' perceptual cognition through text mining can assist designers in better understanding users' perceptual needs, resulting in designed products that are more likely to meet users' expectations for satisfaction. A design approach that can increase users' psychological acceptance of products and boost their competitiveness is the perceptual design method, which combines human and artificial intelligence.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.