Robotics & Machine Learning Daily News2024,Issue(Mar.12) :34-35.

University of Ioannina Researchers Release New Study Findings on Machine Learnin g (AliAmvra-Enhancing Customer Experience through the Application of Machine Lea rning Techniques for Survey Data Assessment and Analysis)

Robotics & Machine Learning Daily News2024,Issue(Mar.12) :34-35.

University of Ioannina Researchers Release New Study Findings on Machine Learnin g (AliAmvra-Enhancing Customer Experience through the Application of Machine Lea rning Techniques for Survey Data Assessment and Analysis)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence.According to news reporting originating from Ioannina,Greece,by NewsRx correspondents,research stated,"AliAmvra is a project developed to explore and promote high-quality catches of the Amvrakikos Gulf (GP) to Artas' w ider regions.In addition,this project aimed to implement an integrated plan of action to form a business identity with high added value and achieve integrated business services adapted to the special characteristics of the area." Our news journalists obtained a quote from the research from University of Ioann ina:"The action plan for this project was to actively search for new markets,c reate a collective identity for the products,promote their quality and added va lue,engage in gastronomes and tasting exhibitions,dissemination and publicity actions,as well as enhance the quality of the products and markets based on the customer needs.The primary focus of this study is to observe and analyze the d ata retrieved from various tasting exhibitions of the AliAmvra project,with a t arget goal of improving customer experience and product quality.An extensive an alysis was conducted for this study by collecting data through surveys that took place in the gastronomes of the AliAmvra project.Our objective was to conduct two types of reviews,one focused in data analysis and the other on evaluating m odel-driven algorithms.Each review utilized a survey with an individual structu re,with each one serving a different purpose.In addition,our model review foc used its attention on developing a robust recommendation system with said data.The algorithms we evaluated were MLP (multi-layered perceptron),RBF (radial bas is function),GenClass,NNC (neural network construction),and FC (feature const ruction),which were used for the implementation of the recommendation system."

Key words

University of Ioannina/Ioannina/Greece/Europe/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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