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A Hybrid Recommendation Architecture for NigerianOnline Stores

机译:NigerianOnline商店的混合推荐体系结构

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摘要

Online retailing, a business activity in e-commerce, is the process of selling physical goods on the internet while online shopping is the process of buying and selling goods and services over the internet. Item recommendations, however, is a business strategy in e-commerce employed in promoting goods sold on an online store. Majority of the online stores in Nigeria have their shopping systems implemented similar to online shopping systems used Developed Countries. Much focus have been placed on the provision of non-personalized recommendations in Nigerian online stores, as ratings information needed for personalized recommendations is sparse. These systems are mostly a hybrid of content-based and collaborative filtering approaches to recommendation generation. The use of content-based, collaborative and demographic hybrids have not been fully explored and implemented. This paper, however, proposes a hybrid item recommendation architecture that combines the content-based, collaborative and demographic filtering approaches in a mixed hybridization strategy for provision of recommendations on online stores. The architecture provides collaborative recommendations using the vector similarity and adjusted cosine similarity measure. The proposed system will go a long way in providing adequate item recommendation in Nigerian stores.
机译:在线零售是电子商务中的一项商业活动,它是在Internet上出售实物的过程,而在线购物是在Internet上买卖产品和服务的过程。但是,项目推荐是电子商务的一种商业策略,用于促销在线商店中出售的商品。尼日利亚的大多数在线商店都实施了类似于发达国家使用的在线购物系统的购物系统。由于个性化推荐所需的评分信息稀少,因此在尼日利亚的在线商店中,很多注意力都集中在提供非个性化推荐上。这些系统主要是基于内容和协作过滤方法的混合生成建议。基于内容的,协作的和人口统计的混合的使用尚未得到充分探索和实现。但是,本文提出了一种混合项目推荐体系结构,该结构在混合混合策略中结合了基于内容的协作和人口统计过滤方法,以在网上商店中提供建议。该体系结构使用矢量相似度和调整后的余弦相似度度量提供协作建议。拟议的系统将为尼日利亚商店提供足够的商品推荐服务大有帮助。

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