The music domain is among the most important ones for adopting recommender systems
technology. In contrast to most other recommendation domains, which predominantly rely on …

Sequential recommendation (SR) provides personalized contents based on the user's
historical interactions. Previous SR methods focus on introducing temporal signals of …

With the constant growth of information, data sparsity problems, and cold start have become
a complex problem in obtaining accurate recommendations. Currently, authors consider the …

Recently, many researchers in recommender systems have realized that encoding user-item
interactions based on deep neural networks (DNNs) promotes collaborative-filtering (CF)'s …

Nowadays, the use of social information is extending to more and more application domains.
In the field of recommender systems, this information has been exploited in different ways to …

Capturing the topological and temporal information of interactions and predicting future
interactions are crucial for many domains, such as social networks, financial transactions …

摘要个性化推荐系统能够根据用户的个性化偏好和需要, 自动, 快速, 精准地为用户提供其所需的
互联网资源, 已成为当今大数据时代应用最广泛的信息检索系统, 具有巨大的商业应用价值 …

In recent years, group buying has become one popular kind of online shopping activities,
thanks to its larger sales and lower unit price. Unfortunately, seldom research focuses on the …

个性化推荐已成为解决信息过载的最有效手段之一, 也是海量数据挖掘研究领域的热点技术.
然而传统推荐算法往往只使用用户对物品的评分信息, 而缺少对用户与物品潜在特征的综合考虑 …

Music listening preferences at a given time depend on a wide range of contextual factors,
such as user emotional state, location and activity at listening time, the day of the week, the …