Evidence map›Paper›PMID 35205537›Full record

ArticleEntropy (Basel, Switzerland)2022

A Comprehensive and Unified Approach to Web Service Trust Evaluation Based on Uncertainty Methodology.

Junwei Zhang, Deyu Li

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. 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.

Junwei ZhangSchool of Computer and Information Technology, Shanxi University, Taiyuan 030006, China.ORCID 0000-0003-0486-8950
Deyu LiSchool of Computer and Information Technology, Shanxi University, Taiyuan 030006, China.ORCID 0000-0003-2489-9404

Funding

Cultivate Scientific Research Excellence Programs of Higher Education Institutions in Shanxi (CSREP) 2019SK036Key R&D program of Shanxi Province 201903D421041National Natural Science Foundation of China 61806116National Natural Science Foundation of China 61972238National Natural Science Foundation of China 62072294Natural Science Foundation of Shanxi Province 201801D221175Natural Science Foundation of Shanxi Province 201901D211414Postgraduate Education Reform Research Project of Shanxi Province 2021YJJG041Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi(STIP) 2019L0500Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi(STIP) 2021L287
6 · The paper itself

Abstract

Web services have the advantage of being able to generate new value-added services based on existing services. To effectively compose Web services, the composition process necessitates that the services that will participate in a given composite service are more trustworthy than those that provide similar functionality. The trust mechanism appears to be a promising way for determining service selection and composition. Existing trust evaluation approaches do not take into account customer expectations. Based on fuzzy set theory and probability theory, this work proposes a unique Web service trust evaluation approach that is notable for its ability to provide personalized service selection based on customer expectations and preferences. The proposed approach defines trust as a fuzzy notion that is related to prior experiences and ratings, and expresses trust in two different forms. This work mainly solves two key issues in Web service trust architectures, bootstrapping trust for the newcomer services and deriving trust for composite services. The proposed approach combines the solutions to numerous issues in a natural way. The case study and approaches comparison demonstrate that the proposed approach is feasible.

Indexed as

service compositionservice selectiontrust bootstraptrust derivationuncertaintyweb services

Identifiers

PMID35205537
PMCPMC8870970

What OpenQuestion holds

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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.