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Rising fascination towards exploration of recommendation systems

机译:对探索推荐系统的兴趣日益浓厚

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India is gradually moving towards paperless work for which all the projects whether governmental or e-commerce are moving online. It leads to increase huge amount of data and information on the internet. Searching for a particular or preferred service or product through this vast amount of data is the hell of a job for a client or a customer. It spoils a lot of precious time and in this busy world nobody can take risk of wasting time for such purpose. This hindered the progress of electronic medium for business. So, recommendation systems arrived which helped users to direct the search in a particular preferred direction based on some similarity function. This is a two way benefit that is it benefits users to find their desired items as well as also it helps businesses to generate more and more sales. Overall it is fruitful that these systems contribute towards paperless governmental work so that it helps India to become a developed nation. There is a wide scope of research in this field such as dealing with scalability and quality in future recommendation systems. This paper deals with the necessity of increased growth of the research in recommendation system, types of recommendation system and obstacles in the path.
机译:印度正逐步走向无纸化工作,所有项目,无论是政府项目还是电子商务项目,都在网上进行。这导致在互联网上增加大量的数据和信息。通过海量数据搜索特定或偏爱的服务或产品对于客户或客户来说是一件艰辛的工作。它浪费了很多宝贵的时间,在这个繁忙的世界中,没有人会为此浪费时间。这阻碍了商业电子媒体的发展。因此,出现了推荐系统,该系统可以帮助用户基于一些相似性功能将搜索引导到特定的首选方向。这有两个好处,既可以使用户找到所需的商品,也可以帮助企业产生越来越多的销售额。总体而言,这些系统为无纸化政府工作做出了贡献,从而有助于印度成为发达国家。在该领域中有广泛的研究,例如在未来推荐系统中处理可伸缩性和质量。本文提出了增加推荐系统研究的必要性,推荐系统的类型和发展道路上的障碍。

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