Multi-Source Pointer Network for Product Title Summarization

August 21, 2018 ยท Declared Dead ยท ๐Ÿ› International Conference on Information and Knowledge Management

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Authors Fei Sun, Peng Jiang, Hanxiao Sun, Changhua Pei, Wenwu Ou, Xiaobo Wang arXiv ID 1808.06885 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.IR Citations 50 Venue International Conference on Information and Knowledge Management Last Checked 3 months ago
Abstract
In this paper, we study the product title summarization problem in E-commerce applications for display on mobile devices. Comparing with conventional sentence summarization, product title summarization has some extra and essential constraints. For example, factual errors or loss of the key information are intolerable for E-commerce applications. Therefore, we abstract two more constraints for product title summarization: (i) do not introduce irrelevant information; (ii) retain the key information (e.g., brand name and commodity name). To address these issues, we propose a novel multi-source pointer network by adding a new knowledge encoder for pointer network. The first constraint is handled by pointer mechanism. For the second constraint, we restore the key information by copying words from the knowledge encoder with the help of the soft gating mechanism. For evaluation, we build a large collection of real-world product titles along with human-written short titles. Experimental results demonstrate that our model significantly outperforms the other baselines. Finally, online deployment of our proposed model has yielded a significant business impact, as measured by the click-through rate.
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