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Trust-based Service Recommendation in Social Network |
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PP: 1567-1574 |
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Author(s) |
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Shuiguang Deng,
Longtao Huang,
Yuyu Yin,
Weitong Tang,
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Abstract |
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| With the number of Web services increasing constantly on the Internet, how to recommend personalized Web services
for users has become more and more important. At present, there emerged some service recommendation systems utilizing influence
ranking and collaborative filtering algorithms in service recommendation. However, they neither considered trust relationships among
users, nor deal with the cold start problem very well. Fortunately, the popularity of social network in nowadays brings a good alternative
for service recommendation to avoid those. In this study, we propose a social network-based service-recommendation method, which
considers users’ history service invocation behaviors, users preferences as well as trust relationships among users implied in social
network and users comments/reviews on services. We have applied this method in a data set extracted from www.epinions.com. A
series of experiments on 86,719 users, 604,190 user trust-relationships and 963,591 reviews on 292,713 services/produces show that
this recommendation method get better recall rate, precision, f-measure and rank score. |
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