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A graph-based context-aware requirement elicitation approach in smart product-service systems

机译：智能产品服务系统中基于图形的上下文感知要求诱导方法

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The paradigm of Smart product-service systems (Smart PSS) has emerged recently owing to the edge-cutting Information and Communication Technology (ICT) and artificial intelligence (AI) techniques. The unique features of Smart PSS including smartness and connectedness, value co-creation and data-driven design manner, enable the collection and analysis of large volume and heterogeneous contextual data to extract useful knowledge. Therefore, requirement elicitation, as a critical process for new solution (i.e. product-service) design, can be conducted in a rather context-aware manner, assured by those massive user-generated data and product-sensed data during the usage stage. Nevertheless, despite a few works on semantic modelling, scarcely any reports on such mechanism in today's smart, connected environment. Aiming to fill this gap, for the first time, a graph-based context-aware requirement elicitation approach considering contextual information within the Smart PSS is proposed. It leverages the pre-defined product, service, and condition ontologies together with Deepwalk technique, to formulate those concepts as nodes and their relationships as the edge of the proposed requirement graph. Implicit stakeholder requirements within a specific context can be further derived based on such interrelationships in a data-driven manner. To demonstrate its feasibility and effectiveness, an example of smart bike share system is addressed to illustrate the requirement elicitation process. It is hoped that this explorative study can offer valuable insights for the service providers who would like to extract requirements not only from the voice of customers but also from the user-generated data and product-sensed data.
机译：最近由于边缘切割信息和通信技术（ICT）和人工智能（AI）技术而出现了智能产品 - 服务系统（SMART PSS）的范式。智能PSS的独特功能，包括智能性和关联，价值共同创建和数据驱动的设计方式，使得大量和异构语境数据的收集和分析能够提取有用的知识。因此，作为新解决方案（即产品 - 服务）设计的关键过程，要求引出可以以相当背景感知的方式进行，通过在使用阶段期间通过这些大规模用户生成的数据和产品感测数据来进行。尽管如此，尽管有一些关于语义建模的作品，但几乎没有关于当今聪明，连通环境中这种机制的报告。提出了考虑智能PSS内的上下文信息的基于图的基于图的上下文感知要求诱导方法的基于图的上下文感知要求诱导方法。它利用预定义的产品，服务和条件本体以及深途化技术，将这些概念作为节点及其与所提出的要求图的边缘一起制定。可以基于以数据驱动方式的这种相互关系进一步派生特定上下文中的隐式利益相关者要求。为了展示其可行性和有效性，解决了智能自行车份额系统的示例，以说明要求阐述过程。希望这项探索性研究可以为希望不仅从客户的声音提取的服务提供商提供有价值的见解，也可以从用户生成的数据和产品感测数据中提取要求。

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