协同过滤推荐瓶颈问题研究

Research on Collaborative Filtering Recommendation Bottleneck Problem

进入21世纪以来,我国的科学技术取得了巨大进步,互联网和电子商务正处于迅猛发展的阶段,促进信息化不断深入到人们的日长生活工作当中。在现代社会中人们的工作繁忙,在购物方面越来越多偏向于在电子商务网站上进行,在享受足不出户的便利的同时,也因为电子商务网站所提供的大量商品造成严重的"信息超载",于是就出现了电子商务推荐系统。其中协同过滤推荐是目前最为常用的电子商务推荐系统,它已经被广泛应用于各商务网站中,但是在使用过程中还存在许多的问题,这些协同过滤推荐瓶颈问题严重阻碍了它的进一步发展。因此,文章的主旨就是针对协同过滤推荐瓶颈问题进行研究,并提出相对应的解决措施清扫阻碍。

The 21 st century, our country has made great progress of science and technology, the Internet and e-commerce is in rapid development stage, promote the informatization continuously go deep into the People's Daily life long work. In modern society people's job is busy, in terms of shopping more and more favor in e-commerce site, enjoying the housebound convenient at the same time, also because e-commerce sites provide a large number of goods caused serious 'information overload', hence the e-commerce recommendation system.The collaborative filtering recommendation is currently the most commonly used e-commerce recommender system, it has been widely applied to an e-commerce site, but many problems still exist in the process of using, the collaborative filtering recommendation bottleneck seriously hindered the further development of it. Therefore, the purpose of this article is in view of the collaborative filtering recommendation bottleneck problem, and put forward the corresponding solutions for cleaning the block.