Recommender systems have been evaluated in many, often incomparable, ways. In this
article, we review the key decisions in evaluating collaborative filtering recommender …

对现有的推荐系统评价指标进行了系统的回顾, 总结了推荐系统评价指标的最新研究进展,
从准确度, 多样性, 新颖性及覆盖率等方面进行多角度阐述, 并对各自的优缺点以及适用环境进行 …

The explosive growth of Internet applications and content, during the last decade, has
revealed an increasing need for information filtering and recommendation. Most research in …

The increasing availability of large-scale location traces creates unprecedent opportunities
to change the paradigm for knowledge discovery in transportation systems. A particularly …

As wireless communication advances, research on location-based services using mobile
devices has attracted interest, which provides information and services related to user's …

The GPS technology and new forms of urban geography have changed the paradigm for
mobile services. As such, the abundant availability of GPS traces has enabled new ways of …

Internet-based recommender systems have traditionally employed collaborative filtering
techniques to deliver relevant" digital" results to users. In the mobile Internet however …

Recommender systems, which recommend items of information that are likely to be of
interest to the users, and filter out less favored data items, have been developed …

The volume of course-related information available to students is rapidly increasing. This
abundance of information has created the need to help students find, organize, and use …

User participation emerged as a critical issue for collaborative and social recommender
systems as well as for a range of other systems based on the power of user community. A …