A research division plays an important role of driving innovation in an organization. Drawing insights, following trends, keeping abreast of new research, and formulating strategies are increasingly becoming more challenging for both researchers and executives as the amount of information grows in both velocity and volume. In this paper we present a use case of how a corporate research community, IBM Research, utilizes Semantic Web technologies to induce a unified Knowledge Graph from both structured and textual data obtained by integrating various applications used by the community related to research projects, academic papers, datasets, achievements and recognition. In order to make the Knowledge Graph more accessible to application developers, we identified a set of common patterns for exploiting the induced knowledge and exposed them as APIs. Those patterns were born out of user research which identified the most valuable use cases or user pain points to be alleviated. We outline two distinct scenarios: recommendation and analytics for business use. We will discuss these scenarios in detail and provide an empirical evaluation on entity recommendation specifically. The methodology used and the lessons learned from this work can be applied to other organizations facing similar challenges.
翻译:研究司在推动一个组织的创新方面发挥着重要作用。随着信息量在速度和数量上的增长,一个研究司在推动一个组织的创新方面发挥着重要的作用。随着趋势的发展、跟上新的研究的步伐和制定战略,对研究人员和行政人员越来越具有挑战性。在本文件中,我们介绍了公司研究界IBM Research如何利用Semantic Web技术从结构化和文字化的数据中产生一个统一的知识图。通过整合社区在研究项目、学术论文、数据集、成就和认识方面使用的各种应用,我们从中获得了这些结构化和文字化的数据。为了使应用者更容易获得知识图,我们确定了一套共同模式,用以利用所引出的知识,并将它们作为AIPI。这些模式产生于用户研究,确定了最有价值的使用案例或用户疼痛点,我们概述了两种不同的情景:建议和供商业使用的分析。我们将详细讨论这些情景,并具体就实体建议提供经验性评价。使用的方法和从这项工作中吸取的经验教训可以适用于面临类似挑战的其他组织。