Solving Cold Start Problem using MBA

被引：0

作者：

Mishra, Nitin Kumar

Mishra, Vimal ^{[1
]}

Chaturvedi, Saumya ^{[2
]}

机构：

[1] IERT Allahabad, Allahabad, Uttar Pradesh, India

[2] AKTU Lucknow, Lucknow, Uttar Pradesh, India

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON POWER, CONTROL, SIGNALS AND INSTRUMENTATION ENGINEERING (ICPCSI) | 2017年

关键词：

Recommender systems; cold-start problem; MBA; Associative rule mining;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recommendation System is the base of Ecommerce business in India and World. After The advent of 4G technology in developed and developing countries people are using internet more than ever. Lot of options are available for almost everything on Internet. People are confused with all the options. Recommendation system makes this easier by giving users options on the basis of history of the user in the system. Now you can get choices on the basis of your likes and dislikes. But this recommendation system fails when we have no information about the user and item. In simple words because we do not have user history therefore we cannot use recommendation algorithm. In this paper we are suggesting a MBA (market basket Analysis) technique to help us solve this problem to some level. We are using data available by Amazon to develop and test our method.

引用

页码：1598 / 1601

页数：4

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