2019
AAAI
AAAI 2019
Automatic Generation of Chinese Short Product Titles for Mobile Display
Abstract
Abstract This paper studies the problem of automatically extracting a short title from a manually written longer description of Ecommerce products for display on mobile devices. It is a new extractive summarization problem on short text inputs, for which we propose a feature-enriched network model, combining three different categories of features in parallel. Experimental results show that our framework significantly outperforms several baselines by a substantial gain of 4.5%. Moreover, we produce an extractive summarization dataset for Ecommerce short texts and will release it to the research community.
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Conference Pioneer
— AAAI 2019
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— short text input
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Generation > Summarization
Natural Language Processing > Generation > Text Generation
Natural Language Processing > Applications > Summarization
Natural Language Processing > Applications > Text Generation
Machine Learning > Learning Types > Deep Learning
Deep Learning > Learning Types > Representation Learning