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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Wang, Yiting Wei, Lifen Xian Univ Technol Sch Econ & Management Xian Peoples R China

ISBN: (纸本)9783031807749;9783031807756

This paper aims to optimize the vehicle-cargo matching of the logistics platform through the hybrid recommendation algorithm to achieve the effective matching between vehicle and cargo sources. This paper constructs a hybrid recommendation model taken into account the content-based recommendation algorithm and the item-based collaborative filtering algorithm. The content-based recommendation algorithm has advantages in matching the inherent attributes of vehicle and cargo sources, whereas the item-based collaborative filtering can deal with the problem of interest drift, and the advantages of these two algorithms are integrated in the hybrid model in this paper. The matching factors are pick out from the data of current logistics platforms, and the feedback competition method is applied for the calculation of the weights, and then the weight similarity is worked out for the recommendation. Multiple aspects are considered in the hybrid model, so as to satisfy the users by recommendation results, thereby achieving vehicle-cargo matching. This paper focuses on the matching of vehicles and cargoes in multiple dimensions, where the personalized and diversified comprehensive recommendation results are acquired to meet the needs of car owners and cargo owners.

关键词： Vehicle-cargo matching Hybrid recommendation algorithm Logistics content-based recommendation algorithm

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Design of Hybrid recommendation algorithm in Online Shopping System

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Journal of New Media 2021年第4期3卷 119-128页

作者： Yingchao Wang Yuanhao Zhu Zongtian Zhang Huihuang Liu Peng Guo Hunan University of Finance and Economics ChangshaChina University Malaysia Sabah Kota KinabaluMalaysia

In order to improve user satisfaction and loyalty on e-commerce websites,recommendation algorithms are used to recommend products that may be of interest to ***,the accuracy of the recommendation algorithm is a primary *** far,there are three mainstream recommendation algorithms,content-based recommendation algorithms,collaborative filtering algorithms and hybrid recommendation ***-based recommendation algorithms and collaborative filtering algorithms have their own *** content-based recommendation algorithm has the problem of the diversity of recommended items,while the collaborative filtering algorithm has the problem of data sparsity and *** the basis of these two algorithms,the hybrid recommendation algorithm learns from each other’s strengths and combines the advantages of the two algorithms to provide people with better *** article will focus on the use of a content-based recommendation algorithm to mine the user’s existing interests,and then combine the collaborative filtering algorithm to establish a potential interest model,mix the existing and potential interests,and calculate with the candidate search content *** similarity gets the recommendation list.

关键词： recommendation algorithm hybrid recommendation algorithm content-based recommendation algorithm collaborative filtering algorithm

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