Evidence map›Paper›PMID 40403084›Full record

ArticlePloS one2025

The role of product art design based on a fuzzy decision support system in improving user interaction experience.

Yuqiao Liu, Shuai Zhang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yuqiao LiuArt and Design College, Shenyang Ligong University, Shenyang, China.
Shuai ZhangArt and Design College, Shenyang Ligong University, Shenyang, China.ORCID https://orcid.org/0009-0008-2026-8924

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

User interaction for product selection relies on its design and technical support to improve the quality of the experience. Decision support systems are incorporated to leverage user experience through product interactions. This article introduces an interaction-based fuzzy decision support (FDS) system to meet user demands in product design through suggestions for user interaction. The proposed system models the maximum possible interaction features through previous user experiences and reviews. Based on these two factors, the fuzzy decisions for interaction improvement or product design modification are identified through likelihood. This likelihood is a variant between lower and higher fuzzy combinations for maximum interaction pursued by the user. The fuzzy process develops multiple higher-order recommendation variants from the interaction computed to improve the user experience. The lower-order variants recommend different product design features to increase the interaction rate. Thus, the decision process determines the need for adaptability through interactive platforms to achieve a better experience. This methodology aimed to improve the interaction rate of 97.4% with better impacts on product design and modification using likelihood variants. The user experience assessment is performed using the higher-order variants with a better user adaptability rate of 98.9%, maximizing the recommendations.

Indexed as

Decision Support TechniquesFuzzy LogicAlgorithmsHumansUser-Computer Interface

Identifiers

PMID40403084
PMCPMC12097716

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.