论文标题
阅读您的需求：基于方面的可控意见摘要旅游评论
Read what you need: Controllable Aspect-based Opinion Summarization of Tourist Reviews
论文作者
论文摘要
手动从大量用户生成的文本中提取相关方面和意见是一个耗时的过程。另一方面，摘要可以帮助有限时间预算的读者快速消耗数据中的关键想法。但是，用于多文件摘要的最新方法，在生成摘要时不会考虑用户偏好。在这项工作中，我们认为需求并提出了一种解决方案，以从大量在线旅游评论中产生个性化的基于方面的意见摘要。我们让读者决定并控制摘要的几个属性，例如感兴趣的长度和特定方面。具体来说，我们采用一种无监督的方法来从TripAdvisor上发布的旅游评论中提取连贯的方面。然后，我们提出了基于整数线性编程（ILP）的提取技术，以选择围绕已确定的方面的意见子集，同时尊重各种控制参数的用户指定值。最后，我们使用众包和基于胭脂的指标评估和比较摘要，并获得竞争结果。
Manually extracting relevant aspects and opinions from large volumes of user-generated text is a time-consuming process. Summaries, on the other hand, help readers with limited time budgets to quickly consume the key ideas from the data. State-of-the-art approaches for multi-document summarization, however, do not consider user preferences while generating summaries. In this work, we argue the need and propose a solution for generating personalized aspect-based opinion summaries from large collections of online tourist reviews. We let our readers decide and control several attributes of the summary such as the length and specific aspects of interest among others. Specifically, we take an unsupervised approach to extract coherent aspects from tourist reviews posted on TripAdvisor. We then propose an Integer Linear Programming (ILP) based extractive technique to select an informative subset of opinions around the identified aspects while respecting the user-specified values for various control parameters. Finally, we evaluate and compare our summaries using crowdsourcing and ROUGE-based metrics and obtain competitive results.
