Clickstream & behavioral analysis with context awareness for e-commercial applications

Sakshi Bansal, Chetna Gupta, Adwitiya Sinha
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引用次数: 6

Abstract

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.
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点击流和行为分析与上下文意识的电子商务应用程序
互联网的广泛普及对商业领域的变革起着至关重要的作用。在购买之前,人们会花很多时间在网上收集信息和反馈,以便更好地指导他们的决定。由于顾客并不亲自出现在商店中,他们可以很容易地通过在线门户从一个供应商转移到另一个供应商。从商业的角度来看,这可能对贸易商的利润和宣传有害。在本研究中,主要关注的是如何克服贸易行业所面临的这些问题。我们提出的模型分析在线用户的“点击流事件”以及一组上下文细节,以提供更好的推荐。记录多个用户的行为可以帮助行业发现用户的习惯和倾向,从而做出更好、更有效的决策,从而提高企业利润和市场覆盖率。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。执行购物篮分析,帮助用户在购买产品和已经购买的物品时进行适当的选择,从而提供更好的购买体验。
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