Abstract
We have presented a new algorithm for generating trust networks based on user tagging information to make recommendations in the online environment. The experiment results showed that this tag-based similarity approach performs better while making recommendations than the traditional collaborative filtering based approach. This proposed technique will be very helpful to deal with data sparsity problems; even when explicit trust rating data is unavailable. The finding will contribute in the area of recommender systems by improving the overall quality of automated recommendation making.
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Bhuiyan, T. (2013). Conclusions. In: Trust for Intelligent Recommendation. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6895-0_7
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DOI: https://doi.org/10.1007/978-1-4614-6895-0_7
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Publisher Name: Springer, New York, NY
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Online ISBN: 978-1-4614-6895-0
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