Automatic Generation of Chinese Short Product Titles for Mobile Display
Yu Gong, Xusheng Luo, Kenny Q. Zhu, Wenwu Ou, Zhao Li, Lu Duan

TL;DR
This paper introduces a feature-enriched network model for automatically generating concise Chinese product titles from longer descriptions, improving summarization accuracy for mobile display in e-commerce.
Contribution
It proposes a novel extractive summarization model combining multiple features and provides a new dataset for e-commerce short text summarization.
Findings
Model outperforms baselines by 4.5%
Significant improvement in summarization accuracy
Dataset released for research community
Abstract
This paper studies the problem of automatically extracting a short title from a manually written longer description of E-commerce 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 E-commerce short texts and will release it to the research community.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Advanced Text Analysis Techniques
