Title | ||
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When E-commerce Meets Social Media: Identifying Business on WeChat Moment Using Bilateral-Attention LSTM. |
Abstract | ||
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WeChat Business, developed on WeChat, the most extensively used instant messaging platform in China, is a new business model that bursts into people's lives in the e-commerce era. As one of the most typical WeChat Business behaviors, WeChat users can advertise products, advocate companies and share customer feedback to their WeChat friends by posting a WeChat Moment--a public status that contains images and a text. Given its popularity and significance, in this paper, we propose a novel Bilateral-Attention LSTM network (BiATT-LSTM) to identify WeChat Business Moments based on their texts and images. In particular, different from previous schemes that equally consider visual and textual modalities for a joint visual-textual classification task, we start our work with a text classification task based on an LSTM network, then we incorporate a bilateral-attention mechanism that can automatically learn two kinds of explicit attention weights for each word, namely 1) a global weight that is insensitive to the images in the same Moment with the word, and 2) a local weight that is sensitive to the images in the same Moment. In this process, we utilize visual information as a guidance to figure out the local weight of a word in a specific Moment. Two-level experiments demonstrate the effectiveness of our framework. It outperforms other schemes that jointly model visual and textual modalities. We also visualize the bilateral-attention mechanism to illustrate how this mechanism helps joint visual-textual classification.
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Year | DOI | Venue |
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2018 | 10.1145/3184558.3186346 | WWW '18: The Web Conference 2018
Lyon
France
April, 2018 |
DocType | ISBN | Citations |
Conference | 978-1-4503-5640-4 | 1 |
PageRank | References | Authors |
0.35 | 9 | 4 |
Name | Order | Citations | PageRank |
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Tianlang Chen | 1 | 12 | 3.31 |
Yuxiao Chen | 2 | 10 | 3.84 |
Han Guo | 3 | 125 | 10.98 |
Jiebo Luo | 4 | 6314 | 374.00 |