Among the applications of Web 2.0, social networking sites continue to proliferate and the volume of content keeps growing; as a result, information overload causes difficulty for users attempting to choose useful and relevant information. In this work, we propose a novel recommendation method based on different types of influences: social, interest and popularity, using personal tendencies in regard to these three decision factors to recommend photos in a photo-sharing website, Flickr. Because these influences have different degrees of impact on each user, the personal tendencies related to these three influences are regarded as personalized weights; combining influence scores enables predicting the scores of items. The experimental results show that our proposed methods can improve the quality of recommendations. © Springer-Verlag Berlin Heidelberg 2013.
CITATION STYLE
Lai, C. H., Liu, D. R., & Liu, M. L. (2013). Recommendations based on different aspects of influences in social media. Lecture Notes in Business Information Processing, 152, 194–201. https://doi.org/10.1007/978-3-642-39878-0_18
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