Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

摘要互联网技术的迅猛发展把我们带进了信息爆炸的时代. 海量信息的同时呈现,
一方面使用户很难从中发现自己感兴趣的部分, 另一方面也使得大量少人问津的信息成为网络中 …

Abstract Most existing Collaborative Filtering (CF) algorithms predict a rating as the
preference of an active user toward a given item, which is always a decimal fraction …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

This paper presents an overview of the field of recommender systems and describes the
current generation of recommendation methods that are usually classified into the following …

Collaborative recommendation approaches based on nearest-neighbors are still highly
popular today due to their simplicity, their efficiency, and their ability to produce accurate and …

A recommender system must be able to suggest items that are likely to be preferred by the
user. In most systems, the degree of preference is represented by a rating score. Given a …

Most of existing e-commerce recommender systems aim to recommend the right product to a
user, based on whether the user is likely to purchase or like a product. On the other hand …

Neighborhood-based collaborative filtering algorithms, also referred to as memory-based
algorithms, were among the earliest algorithms developed for collaborative filtering. These …