论文标题

利用微博来通过匹配的资源需求和可用性来协助污点后救济操作

Utilizing Microblogs for Assisting Post-Disaster Relief Operations via Matching Resource Needs and Availabilities

论文作者

Dutt, Ritam, Basu, Moumita, Ghosh, Kripabandhu, Ghosh, Saptarshi

论文摘要

在灾难活动中,两种对于协调救济操​​作特别有用的信息是受影响地区的资源的需求和资源的可用性(例如食品,水,药物)。在微博网站上发布的信息越来越多地用于协助污水爆发后的救济操作。在这种情况下,两个实际的挑战是(i)〜要确定有关资源需求和可用性(分别称为需求的启动和可用性 - 特威)的推文,以及(ii)〜以与适当的可用性自动匹配需求。尽管有几项工作解决了第一个问题,但几乎没有关于自动匹配需求与可用性的工作。尝试匹配的几个先前的作品仅考虑了资源,并且没有尝试了解在实践中对匹配至关重要的需求/可用性的其他方面。在这项工作中,我们开发了一种理解需求特性和可用性特征的五个重要方面的方法,包括需要/可用的数量/可用数量,需求/可用性的地理位置以及需要/提供资源的人。理解这些方面有助于我们解决需求可用性匹配问题,不仅考虑了资源,还考虑了其​​他因素,例如需求与可用性之间的地理距离。据我们所知,这项研究是开发理解需求特性和可用性特征语义的方法的首次尝试。我们还考虑了资源相似性和地理邻近性,还开发了一种新颖的方法,用于将需求特性与可用性 - 饰面相匹配。在两个与两个灾难事件相对应的数据集上进行的实验表明,我们所提出的方法的匹配性能要比先前的工作中的匹配更好。

During a disaster event, two types of information that are especially useful for coordinating relief operations are needs and availabilities of resources (e.g., food, water, medicines) in the affected region. Information posted on microblogging sites is increasingly being used for assisting post-disaster relief operations. In this context, two practical challenges are (i)~to identify tweets that inform about resource needs and availabilities (termed as need-tweets and availability-tweets respectively), and (ii)~to automatically match needs with appropriate availabilities. While several works have addressed the first problem, there has been little work on automatically matching needs with availabilities. The few prior works that attempted matching only considered the resources, and no attempt has been made to understand other aspects of needs/availabilities that are essential for matching in practice. In this work, we develop a methodology for understanding five important aspects of need-tweets and availability-tweets, including what resource and what quantity is needed/available, the geographical location of the need/availability, and who needs / is providing the resource. Understanding these aspects helps us to address the need-availability matching problem considering not only the resources, but also other factors such as the geographical proximity between the need and the availability. To our knowledge, this study is the first attempt to develop methods for understanding the semantics of need-tweets and availability-tweets. We also develop a novel methodology for matching need-tweets with availability-tweets, considering both resource similarity and geographical proximity. Experiments on two datasets corresponding to two disaster events, demonstrate that our proposed methods perform substantially better matching than those in prior works.

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