Abstract
In social network services, the relationship among members can be represented as link network, and the link prediction problem is to infer the value of such links. By analysing the structure of link network, researchers have proposed several methods for solving link prediction. Nowdays, when some members label their link values, they also make comments, which have been seldom considered for link prediction. In this paper, by considering both the link network data and user comment data, we propose multimodal deep belief network based link prediction method, which outperforms other state-of-art methods. With the learned joint distribution of link network features and user comment features, our method could generate comment words properly.
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Fan, R.E., Chang, K.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: Liblinear: a library for large linear classification. J. Mach. Learn. Res. 9, 1871–1874 (2008)
Glorot, X., Bordes, A., Bengio, Y.: Domain adaptation for large-scale sentiment classification: a deep learning approach. In: Proceedings of the 28th International Conference on Machine Learning (ICML-2011), pp. 513–520 (2011)
Hinton, G.E.: Training products of experts by minimizing contrastive divergence. Neural Comput. 14(8), 1771–1800 (2002)
Hinton, G.E.: To recognize shapes, first learn to generate images. Prog. Brain Res. 165, 535–547 (2007)
Kiros, R., Salakhutdinov, R., Zemel, R.: Multimodal neural language models. In: Proceedings of the 31st International Conference on Machine Learning (ICML-14), pp. 595–603 (2014)
Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. J. Am. Soc. Inf. Sci. Technol. 58(7), 1019–1031 (2007)
Liu, F., Liu, B., Sun, C., Liu, M., Wang, X.: Deep learning approaches for link prediction in social network services. In: Lee, M., Hirose, A., Hou, Z.-G., Kil, R.M. (eds.) ICONIP 2013, Part II. LNCS, vol. 8227, pp. 425–432. Springer, Heidelberg (2013)
Liu, F., Liu, B., Sun, C., Liu, M., Wang, X.: Deep belief network-based approaches for link prediction in signed social networks. Entropy 17(4), 2140–2169 (2015)
Liu, F., Liu, B., Wang, X., Liu, M., Wang, B.: Features for link prediction in social networks: A comprehensive study. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1706–1711. IEEE (2012)
Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retrieval 2(1), 1–135 (2008)
Srivastava, N., Salakhutdinov, R.R.: Multimodal learning with deep boltzmann machines. In: Advances in neural information processing systems, pp. 2222–2230 (2012)
Wang, B., Liu, B., Wang, X., Sun, C., Zhang, D.: Deep learning approaches to semantic relevance modeling for chinese question-answer pairs. ACM Trans. Asian Lang. Inf. Process. (TALIP) 10(4), 21–37 (2011)
Wang, P., Xu, B., Wu, Y., Zhou, X.: Link prediction in social networks: the state-of-the-art. Sci. China Inf. Sci. 58(1), 1–38 (2014)
West, R., Paskov, S.H., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Trans. Assoc. Comput. Linguist. 2(1), 297–310 (2014)
Zhou, S., Chen, Q., Wang, X.: Fuzzy deep belief networks for semi-supervised sentiment classification. Neurocomputing 131, 312–322 (2014)
Acknowledgement
This work is supported by the National Natural Science Foundation of China (61272383, 61300114, and 61572151), Specialized Research Fund for the Doctoral Program of Higher Education (No. 20132302120047), the Special Financial Grant from the China Postdoctoral Science Foundation (No. 2014T70340), and China Postdoctoral Science Foundation (No. 2013M530156).
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Liu, F., Liu, B., Sun, C., Liu, M., Wang, X. (2015). Multimodal Deep Belief Network Based Link Prediction and User Comment Generation. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_3
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DOI: https://doi.org/10.1007/978-3-319-26561-2_3
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