|
G. Adomavicius and A. Tuzhilin. Context-Aware Recommender Systems. Recommender Systems Handbook, Springer US, 2011, pages 217–253. J. A. Bullinaria and J. P. Levy. Extracting semantic representations from word cooccurrence statistics: a computational study. Behavior Research Methods, 39 3:510–26, 2007. C.-M. Chen, M.-F. Tsai, Y.-C. Lin, and Y.-H. Yang. Query-based music recommendations via preference embedding. In Proceedings of the 10th ACM Conference on Recommender Systems, RecSys ’16, pages 79–82. ACM, 2016. K. Choi, G. Fazekas, and M. B. Sandler. Understanding music playlists. CoRR, abs/1511.07004, 2015. J. R. Firth. A synopsis of linguistic theory 1930-55. Studies in Linguistic Analysis (special volume of the Philological Society), 1952-59:1–32, 1957. J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. T. Riedl. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems, 22(1):5–53, Jan 2004. Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. In In IEEE International Conference on Data Mining (ICDM 2008, pages 263–272, 2008. A. L. Maas, R. E. Daly, P. T. Pham, D. Huang, A. Y. Ng, and C. Potts. Learning word vectors for sentiment analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1, HLT ’11, pages 142–150. Association for Computational Linguistics, 2011. T. Mikolov, K. Chen, G. Corrado, and J. Dean. Efficient estimation of word representations in vector space. CoRR, abs/1301.3781, 2013. T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. CoRR, abs/1310.4546, 2013. T. Mikolov, W.-t. Yih, and G. Zweig. Linguistic regularities in continuous space word representations. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 746–751. Association for Computational Linguistics, 2013. B. Perozzi, R. Al-Rfou, and S. Skiena. Deepwalk: Online learning of social representations. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, pages 701–710. ACM, 2014. S. Rendle. Factorization machines with libfm. ACM Transactions on Intelligent Systems and Technology, 3(3):57:1–57:22, May 2012. J. D. M. Rennie and N. Srebro. Fast maximum margin matrix factorization for collaborative prediction. In Proceedings of the 22Nd International Conference on Machine Learning, ICML ’05, pages 713–719. ACM, 2005. J. Tang, M. Qu, M. Wang, M. Zhang, J. Yan, and Q. Mei. Line: Large-scale information network embedding. In Proceedings of the 24th International Conference on World Wide Web, WWW ’15, pages 1067–1077, Republic and Canton of Geneva, Switzerland, 2015. ACM. W. Y. Zou, R. Socher, D. M. Cer, and C. D. Manning. Bilingual word embeddings for phrase-based machine translation. In EMNLP, 2013.
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