Abstract
In this paper, we give a solution to the product prediction shared task of CCKS 2016. The main purpose of the task is to determine the product categories for the import and export transaction record data. For this specific dataset, we apply deep neural networks to solve the multi-label classification problem. On the training set, our proposed method achieves a precision of 0.90, and the proposed model can have a good performance on the test set.
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Acknowledgments
This work has been partially funded by the National Basic Reaseach Program of China (2014CB340404) and the IBM SUR (2015) grant.
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Shijia, E., Xiang, Y. (2016). Product Prediction with Deep Neural Networks. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_25
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DOI: https://doi.org/10.1007/978-981-10-3168-7_25
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