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A Movie E-Shop Recommendation Model Based on Web Usage and Ontological Data

机译:基于网络使用和本体数据的电影网店推荐模型

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摘要

Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today s e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling, and profiling setting up a successful recommendation system is not a trivial or straightforward task This paper argues that by monitoring, analyzing, and understanding the behavior of customers, their demographics, opinions, preferences, andhistory, as well as taking into consideration the specific e-shop ontology and by applying Web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users' interaction, increase its usability, convert users to buyers, retain current customers, and establish long-term and loyal one-to-one relationships.
机译:推荐系统是特殊的个性化工具,可以帮助用户在复杂的网上商店中找到有趣的信息和服务。即使当今的电子商务环境已经发生了巨大的发展,并且现在已经融合了来自其他领域和应用程序领域的技术,例如Web挖掘,语义,人工智能,用户建模和概要分析,但是建立成功的推荐系统并不是一件容易的事或简单的任务。该论文认为,通过监视,分析和理解客户的行为,他们的人口统计,观点,偏好和历史,并考虑到特定的电子商店本体,并通过应用Web挖掘技术,可以产生建议的有效性。明显改善。通过这种方式,电子商店可以提高用户的交互性,提高其可用性,将用户转换为购买者,保留现有客户并建立长期和忠实的一对一关系。

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