基于多属性模型的定制PC推荐网格天际线设计与构建

Q2 Engineering
Designs Pub Date : 2023-08-31 DOI:10.3390/designs7050104
Soo-Yeon Jeong, Junseok Kim, Sun-Young Ihm
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引用次数: 0

摘要

近年来,人们一直在根据自己想要的性能和用途购买定制的个人电脑。然而,对于非技术用户来说,在购买定制PC时,会遇到许多挑战。不专业的人不仅不熟悉计算机设备的术语,而且需要考虑不同计算机设备的许多规范。因此,本文提出了一种在使用skyline购买定制pc时推荐合适设备型号的方法。由于不同的计算机设备有不同的规范,我们需要一种考虑多个属性的方法。Skyline查询是一种考虑对象的多个属性并按照用户满意的顺序对它们进行索引的技术。网格天际线是一种利用基于网格的划分技术,减少现有天际线技术中对象间支配关系的计算次数,从而减少索引构建时间的技术。我们测量了网格天际线和每个计算机设备模型的排行榜结果之间的相似性。实验结果显示,与按电脑设备型号分类的排行榜相比,平均得分为88分(满分100分),与实际的排行榜相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Design and Construction of a Grid Skyline for Custom-Built PC Recommendations Based on a Multi-Attribute Model
In recent years, people have been buying custom-built PCs based on the performance they want and what they will use them for. However, there are many challenges for non-technical users when purchasing a custom-built PC. Not only is the terminology of computer devices unfamiliar to non-experts, but there are many specifications for different computer devices that need to be considered. Therefore, this paper proposes a method for recommending appropriate device models when purchasing custom-built PCs using a skyline. Because different computer devices have different specifications, we need a method that takes into account multiple attributes. Skyline querying is a technique that considers multiple attributes of an object and indexes them in order of user satisfaction. A grid skyline is a technique that uses a grid-based partitioning technique to reduce the number of calculations of the dominance relationship between objects in the existing skyline technique, thus reducing the index construction time. We measured the similarity between the results of the grid skyline and the leaderboard for each model of computer device. As a result of this experiment, compared to the leaderboard categorized by model of computer device, the average score was 88 out of 100, which was similar to the actual leaderboard.
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来源期刊
Designs
Designs Engineering-Engineering (miscellaneous)
CiteScore
3.90
自引率
0.00%
发文量
0
审稿时长
11 weeks
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