A New Approach to Image-Based Recommender Systems with the Application of Heatmaps Maps

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Piotr Woldan, P. Duda, A. Cader, Ivan Laktionov
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引用次数: 0

Abstract

Abstract One of the fundamental issues of modern society is access to interesting and useful content. As the amount of available content increases, this task becomes more and more challenging. Our needs are not always formulated in words; sometimes we have to use complex data types like images. In this paper, we consider the three approaches to creating recommender systems based on image data. The proposed systems are evaluated on a real-world dataset. Two case studies are presented. The first one presents the case of an item with many similar objects in a database, and the second one with only a few similar items.
基于热图的图像推荐系统研究
现代社会的基本问题之一是获取有趣和有用的内容。随着可用内容的增加,这项任务变得越来越具有挑战性。我们的需要并不总是用语言表达;有时我们必须使用复杂的数据类型,如图像。在本文中,我们考虑了三种基于图像数据创建推荐系统的方法。提出的系统在真实世界的数据集上进行了评估。提出了两个案例研究。第一个示例表示数据库中具有许多相似对象的项的情况,第二个示例仅具有少数相似项的情况。
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来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
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