Ultra-Concise Multi-genre Summarisation of Web2.0: towards Intelligent Content Generation

Elena Lloret, E. Boldrini, P. Martínez-Barco, M. Palomar
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引用次数: 1

Abstract

The electronic Word of Mouth has become the most powerful communication channel thanks to the wide usage of the Social Media. Our research proposes an approach towards the production of automatic ultra-concise summaries from multiple Web 2.0 sources. We exploit user-generated content from reviews and microblogs in different domains, and compile and analyse four types of ultra-concise summaries: a)positive information, b) negative information; c) both or d) objective information. The appropriateness and usefulness of our model is demonstrated by its successful results and great potential in real-life applications, thus meaning a relevant advancement of the state-of-the-art approaches.
Web2.0的超简洁多体裁总结:走向智能内容生成
由于社交媒体的广泛使用,电子口碑已经成为最强大的传播渠道。我们的研究提出了一种从多个Web 2.0来源自动生成超简明摘要的方法。我们从不同领域的评论和微博中挖掘用户生成的内容,并编译和分析了四种超简明摘要:a)正面信息,b)负面信息;C)两者都有,还是d)客观信息。我们的模型的适当性和实用性通过其成功的结果和在实际应用中的巨大潜力得到了证明,因此意味着最先进方法的相关进步。
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