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首页> 外文会议>Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on >Mining consumer behaviors in the electronic commerce environment
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Mining consumer behaviors in the electronic commerce environment

机译：挖掘电子商务环境中的消费者行为

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摘要

In the electronic commerce environment, the consumers can purchase products from the internet and the business can easily obtain the data about the transactions. Compared with other commodities, consumable products are purchased high-frequently. Although single gains for consumable products may be lower than that of appliances or electronic products, the accumulative gains for consumable products are great. Therefore, grasping suitable timing to do sales promotion for consumable products is an important task. For the consumable products, the purchase time for the next transaction is usually related to the purchased quantities for this transaction. In this paper, we propose a novel data mining algorithm to find the item-consumption behaviors for most of the consumers. From this information, we can predict the next purchase time for an item based on the purchased quantity of this item at this time. The experimental results show that our algorithm is efficient and scalable, and the mining results can exactly reflect the consumption behaviors for most of the consumers.
机译：在电子商务环境中，消费者可以从Internet购买产品，并且企业可以轻松获得有关交易的数据。与其他商品相比，易耗品的购买频率很高。尽管消费品的单项收益可能低于家用电器或电子产品的单项收益，但消费品的累积收益却很大。因此，把握适当的时机进行消耗品的促销是一项重要的任务。对于消耗品，下一次交易的购买时间通常与该交易的购买数量有关。在本文中，我们提出了一种新颖的数据挖掘算法来查找大多数消费者的商品消费行为。根据此信息，我们可以根据当前商品的购买数量来预测该商品的下一次购买时间。实验结果表明，该算法高效，可扩展，挖掘结果可以准确反映大多数消费者的消费行为。

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