ArticleEnvironmental science and pollution research international2021
A trust-enhanced and preference-aware collaborative method for recommending new energy vehicle.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- How Symbols and Social Interaction Influence the Experienced Utility of Sustainable Lifestyle Guiding Policies: Evidence from Eastern China.International journal of environmental research and public health · 2022Article
- The efficient operating parameter estimation for a simulated plug-in hybrid electric vehicle.Environmental science and pollution research international · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
New energy vehicle (NEV), an Eco-friendly innovation to alleviate the problems of energy scarcity and environmental pollution, is increasingly popular in many countries. Various new energy vehicles are provided with quantity of basic information (e.g., performance, quality, and price), which hinders potential users from effectively finding the most desired or interested new energy vehicles to satisfy their personalized requirements. This paper proposes a three-stage recommendation method for facilitating users to find the proper NEV considering users' preferences and social trust relationship. In the first stage, the users' preferences on evaluation criteria are determined by best-worst method (BWM) through hesitant fuzzy preference comparison vectors. In the second stage, the users' demographic similarity is obtained considering different formats of information, and then users' trust degrees are generated from the entire propagation paths using n dimensional path-ordering-induced order-weighted averaging (NP-IOWA) operator, thereby obtaining the trust-based similarity. In the third stage, the comprehensive user-rating matrix is constructed with the obtained weights, and then, it is combined with the trust-based similarity to recommend NEV based on collaborative filtering technique. A case study is given to illustrate the feasibility of the proposed method and the comparative analysis is conducted to show the advantages of the proposed method.
Indexed as
Identifiers
33043423What 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.