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In recent years, due to the rapid development of e-commerce, personalized recommendation systems have prevailed in product marketing. However, recommendation systems rely heavily on big data, creating a difficult situation for businesses at initial stages of development. We design several methods — including a traditional classifier, heuristic scoring, and machine learning — to build a recommendation...
Recently, location-based social network services have become very popular. Therefore, point of interests (POIs) recommendation has also become a promising and hot research problem. In POIs recommendation, the number of locations could be more than the number of users, so it is a challenge to recommend relevant locations. In this paper, we incorporate user preference, social influence and attraction...
Ten cent Weibo is one of the largest micro-blogging websites in China. There are more than 200 million registered users on Ten cent Weibo, generating over 40 million messages each day. Recommending appealing items to users is a mechanism to reduce the risk of information overload. The task of this paper is to predict whether or not a user will follow an item that has been recommended to the user by...
This paper addresses the topic of social advertising, which refers to the allocation of ads based on individual user social information and behaviors. As social network services (e.g., Facebook and Morgenstern) are becoming the main platform for social activities, more than 20% of online advertisements appear on social network sites. The allocation of advertisements based on both individual information...
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