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講座內(nèi)容：

預(yù)約容量：20

 講座內(nèi)容：

 Part I: The Internet of Things (IoT) allows objects to be sensed and managed over the networks, which creates opportunities for more direct integration between the physical world and computer-based systems. People-centric sensing or social sensing transforms how we sense the world. Today, social sensing (e.g., mobile apps) complements physical sensing (e.g., IoT) by substantially extending the horizon we know about the world in real time. We discuss how we can integrate physical and social sensing to enable better and smarter services. We use city mobility services to demonstrate the potential of the proposed integration.

 Part II: Assessing service quality proves very subjective, varying with objectives, methods, tools, and areas of assessment in the service sector. Customers’ perception of services usually plays an essential role in assessing the quality of services. Mining customers’ opinions in real time becomes a promising approach to the process of capturing and deciphering customers’ perception of their service experiences. We first discuss a big data-mediated approach and system that facilitates capturing, understanding, and evaluation of customers’ perception of provided services in real time. We will explain a big data based framework in support of data retrieving, aggregations, transformations, and visualizations by focusing on public ratings and comments from different data sources. An implementation with smart evaluation services using the US higher education services as an example will be mainly presented. We will also discuss how the proposed approach can be adopted in enhancing applications used in the patient-centric healthcare service community.

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