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Clickstream behavioral analysis with context awareness for e-commercial applications

机译:带有上下文感知的点击流和行为分析,用于电子商务应用程序

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摘要

The widespread eminence of internetworking plays a vital role in revolutionizing the commercial domain. Prior to make purchases, people spend a lot of time on the internet to gather information and feedback, so as to better direct their decisions. Since, customers are not present in person in the stores they can easily shift from one supplier to the other via online portals. From business point of view, this could be harmful for the profit and propaganda of traders. In this research, the prime focus is to overcome such problems confronted by trading industries. Our proposed model analyses `Clickstream Events' of online users along with set of contextual details for providing better recommendations. Recording the behavior of several users can help industries to discover habits and tendencies of user, which can lead to even better and effective decisions to improve business profit and its market coverage. Further, our proposed model aims at discovering the relationship between various items, from the context of user interest. Market Basket Analysis is performed that assists the user with appropriate options while purchasing products along with items already purchased, thereby offering better buying experience.
机译:互联网络的广泛影响在彻底改变商业领域中起着至关重要的作用。在进行购买之前,人们会花大量时间在互联网上收集信息和反馈,以便更好地指导他们的决策。由于客户不在商店中亲自出现,因此他们可以通过在线门户轻松地从一个供应商转移到另一个供应商。从商业角度来看,这可能对交易者的利润和宣传有害。在这项研究中,主要重点是克服贸易行业面临的此类问题。我们提出的模型分析了在线用户的“点击流事件”以及一组上下文详细信息,以提供更好的建议。记录多个用户的行为可以帮助行业发现用户的习惯和趋势,从而可以做出更好,更有效的决策来提高业务利润及其市场覆盖率。此外,我们提出的模型旨在从用户兴趣的上下文中发现各种项目之间的关系。进行市场购物篮分析,以帮助用户在购买产品和已购买商品的同时提供适当的选择,从而提供更好的购买体验。

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