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Constructing and Exploring Composite Items

机译:构建和探索复合物品

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摘要

Nowadays, online shopping has become a daily activity. Web users purchase a variety of items ranging from books to electronics. The large supply of online products calls for sophisticated techniques to help users explore available items. We propose to build composite items which associate a central item with a set of packages, formed by satellite items, and help users explore them. For example, a user shopping for an iPhone (i.e., the central item) with a price budget can be presented with both the iPhone and a package of other items that match well with the iPhone (e.g., {Belkin case, Bose sounddock, Kroo USB cable}) as a composite item, whose total price is within the user's budget. We define and study the problem of effective construction and exploration of large sets of packages associated with a central item, and design and implement efficient algorithms for solving the problem in two stages: summarization, a technique which picks k representative packages for each central item; and visual effect optimization, which helps the user find diverse composite items quickly by minimizing overlap between packages presented to the user in a ranked order. We conduct an extensive set of experiments on Yahoo! Shopping data sets to demonstrate the efficiency and effectiveness of our algorithms.
机译:如今,网上购物已成为日常活动。 Web用户购买从书籍到电子产品的各种项目。大量的在线产品需要复杂的技术,以帮助用户探索可用物品。我们建议构建将中心项目与一组包,由卫星物品组成的组件构建,并帮助用户探索它们。例如,可以使用iPhone和类似物品的IPhone(即,中央项目)的用户购物与iPhone相匹配的其他物品(例如,{Belkin Case,Bose Sounddock,Kroo USB电缆})作为综合项目,其总价格在用户的预算范围内。我们定义和研究与中央项目相关的大型包装的有效建设和探索的问题,以及设计和实施有效的算法,以解决两个阶段的问题:摘要,这是针对每个中央项目选择K代表包的技术;和视觉效果优化,帮助用户通过以排名顺序最小化呈现给用户的包之间的重叠来快速找到多样化的复合项目。我们在雅虎进行广泛的实验!购物数据集以展示算法的效率和有效性。

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