Abstract
It’s a consensus that trust relationship is significant to improve the recommendation efficiently. But in most cases, trust relationship information is so sparse and difficult to use. Actually, the trust relationship is the response of interest among users, that is, it is an effective method to find the appropriate trust relationships by mining users’ interests accurately. There are so many factors that can affect users’ interest as well, such as age, occupation and so on. Based on these factors we can construct a heterogeneous information network, this paper deeply mine more accurate trust relationship through the interest and similarity from the heterogeneous information network among users, and merges the trust relationship to the matrix decomposition techniques. Moreover, we innovative conduct our experiment to test the recommendation algorithm based on trust, which has not been studied so far in MovieLens100k dataset. Experimental results demonstrate that our method outperforms other counterparts both in terms of accuracy.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (No. 71473035), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 14YJA870010), Jilin Provincial Science and Technology Key Project (No. 20150204040GX), Project of Jilin Provincial Industrial Technology Research and Development (No. 2015Y055), National Training Programs of Innovation and Entrepreneurship for Undergraduates (201410200042), Natural Science Fund of Northeast Normal University (2014015KJ004).
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Wang, J., Fei, Z., Qiao, S., Sun, W., Sun, X., Zhang, B. (2016). A Novel Recommendation Method Based on User’s Interest and Heterogeneous Information. In: Morishima, A., et al. Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9865. Springer, Cham. https://doi.org/10.1007/978-3-319-45835-9_8
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DOI: https://doi.org/10.1007/978-3-319-45835-9_8
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