Henry Kautz
Bart Selman
Mehul Shah
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Cross Ref
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Index Terms
- Referral Web: combining social networks and collaborative filtering
Recommendations
Social referral: leveraging network connections to deliver recommendations
RecSys '12: Proceedings of the sixth ACM conference on Recommender systemsMuch work has been done to study the interplay between recommender systems and social networks. This creates a very powerful coupling in presenting highly relevant recommendations to the users. However, to our knowledge, little attention has been paid ...
Receiver responses to referral reward programs in social networks
Because online circumstances allows communication remotely and out of synchronization, along with a better communication capacity, online referral reward programs in social networks may have different characteristics compared with traditional referral ...
Reviews
Maria Teresa Molfino
Referral Web is a prototype of an interactive system that enables users to automatically find chains of experts on a given topic on the Web. To discover direct relationships between individuals, the prototype searches for names in proximity in any documents available on the Web, and builds a graph in which the nodes represent individuals and the edges represent direct relationships between them. Referral Web's main advantage over well-known search engines is that the search is more focused and reliable as the system responds to more complex queries that include names, topics, and social domains. Moreover, it is not limited to any set of topics determined in advance or to the users registered with the service. The system seems to be useful, and the possibility of accessing it on the Web is promising. However, the description of it is quite short, is mainly user-oriented, and emphasizes the social aspect of the application. Moreover, the paper lacks both a discussion of the accuracy of automatic search and a deep explanation of the graph analysis performed during the actual search.
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