Deep Learning-Based Business Recommendation System in Intelligent Vehicles

被引：0

作者：

Yu K. ^{[1
]}

Lim K. ^{[2
]}

Kim P. ^{[1
]}

机构：

[1] Department of Computer Engineering, Chosun University, Gwangju

[2] Department of Computer Science, William Paterson University of New Jersey, Wayne, 07470, NJ

来源：

Mobile Information Systems | 2023年 / 2023卷

关键词：

Deep learning - Image classification - Intelligent vehicle highway systems - Learning systems;

D O I：

10.1155/2023/3704217

中图分类号：

学科分类号：

摘要：

The advancements in intelligent vehicle technologies are facilitating the growth of information technology (IT) platforms, unlike conventional automobiles. In-vehicle-infotainment (IVI) is becoming an appealing element in intelligent vehicles as it offers various experiences to users; however, it requires personalized services to provide even more sophisticated user experiences. It is supposed that passengers search for businesses that provide products or services they found interesting in videos played via IVIs while the vehicle is driving autonomously. In that case, it could be more effective to use images that can express the user's preference as a query for the search than to utilize texts such as product names. Accordingly, this study proposes a recommendation system that informs users of businesses near an intelligent vehicle when a passenger inputs an image of a product or service into an IVI system. The proposed recommendation system involves training deep learning-based image classification models with the user's interest images to classify the category, measure the similarity with the business category using Word2vec, and finally provide the locations of the businesses with a high degree of similarity via IVI, using a smartphone. The experimental results indicated that the user's interest image exhibited 85% accuracy for category classification via the EfficientNet B0 model, while the similarity between the image and business categories using Word2vec was particularly high in the business category similar to the actual image category. © 2023 Kyungho Yu et al.

引用

共 23 条

[11]

Apple, Apple CarPlay

[12]

Google, Android AU

[13]

Ranzenberger T., Hacker C., Gallwitz F., Integration of a Kaldi speech recognizer into a speech dialog system for automotive infotainment applications, Studientexte Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung, 2018, pp. 293-300, (2018)

[14]

Parada-Loira F., Gonzalez-Agulla E., Alba-Castro J.L., Hand Gestures to Control Infotainment Equipment in Cars, pp. 1-6

[15]

Verma B., Choudhary A., Framework for dynamic hand gesture recognition using Grassmann manifold for intelligent vehicles, IET Intelligent Transport Systems, 12, 7, pp. 721-729, (2018)

[16]

Bobadilla J., Alonso S., Hernando A., Deep learning architecture for collaborative filtering recommender systems, Applied Sciences, 10, 7, (2020)

[17]

Zhang B., Zhu M., Yu M., Pu D., Feng G., Extreme residual connected convolution-based collaborative filtering for document context-aware rating prediction, IEEE Access, 8, pp. 53604-53613, (2020)

[18]

Guan Y., Wei Q., Chen G., Deep learning based personalized recommendation with multi-view information integration, Decision Support Systems, 118, pp. 58-69, (2019)

[19]

Gupta G., Katarya R., Research on understanding the effect of deep learning on user preferences, Arabian Journal for Science and Engineering, 46, 4, pp. 3247-3286, (2020)

[20]

Zhang S., Yao L., Sun A., Tay Y., Deep learning based recommender system: A survey and new perspectives, ACM Computing Surveys, 52, 1, pp. 1-38, (2019)

← 1 2 3 →