Recommender systems provide personalized information access to users of Internet
services from social networks to e-commerce to media and entertainment. As is appropriate …

Research on recommender systems (RSs) has traditionally focused on the design of
systems capable of suggesting items of interest for users. However, often the most important …

The explosive popularity of e-commerce sites has reshaped users» shop** habits and an
increasing number of users prefer to spend more time shop** online. This evolution …

Many of today's online services provide personalized recommendations to their users. Such
recommendations are typically designed to serve certain user needs, eg, to quickly find …

We study how an online marketplace's personalized product recommendations and its
consumer profiling accuracy affect third-party sellers' competition and the market outcomes …

Conversion Rate (CVR) prediction in modern industrial e-commerce platforms is becoming
increasingly important, which directly contributes to the final revenue. In order to address the …

Recommender systems are personalized information access applications; they are
ubiquitous in today's online environment, and effective at finding items that meet user needs …

Academic research in the field of recommender systems mainly focuses on the problem of
maximizing the users' utility by trying to identify the most relevant items for each user …

The weighted bipartite-matching problem (WBM) plays a significant role in many real-world
applications, including resource allocation, scheduling, Internet advertising, and E …

ABSTRACT A number of ways exist in which a recommender system can have an impact on
users and business. However, only a small number of them can be reasonably addressed …