Abstract
With the recent advances of information and communication technology, people communicate with each other through online communities or social networking services, such as PatientsLikeMe and Facebook. One of the key challenges in aspects of providing sustainable situation-aware services is how to utilize peoples’ experiences shared as reusable social-intelligence. If domain-specific collective intelligence is well constructed, the knowledge usages can be extended to situation-awareness-based personal situation understanding, and sustainable recommendation services with user intent. In this paper, we introduce a sustainable situation-awareness supporting framework based on text-mining techniques and a domain-specific knowledge model, the so-called Service Quality Model for Hospitals (SQM-H). Different from obtaining sustainable contexts from heterogeneous sensors surrounding users, it aggregates SQM-H based service-specific knowledge from online health communities. Our framework includes a set of components: data aggregation, text-mining, service quality analysis, and open Application Programming Interface (APIs) for recommendation services. Those components have been designed to deal with users’ immediate request, providing service quality related information reflected in collective intelligence and analyzed information based on that along with the SQM-H. As a proof of concept, we implemented a prototype system which interacts with users through smartphone user interface. Our framework supports qualitative and quantitative information based on SQM-H and statistical analyses for the given user queries. Through the implementation and user tests, we confirmed an increased knowledge support for decision-making and an easy mashup with provided Open APIs. We believe that the suggested situation-awareness supporting framework can be applied to numerous sustainable applications related to healthcare and wellness domain areas if domain-specific knowledge models are redesigned.
Highlights
With the development of networks and the spread of smart devices, people are living in an age of flood of information [1]
As a proof of concept for the situation-aware recommendation service based on collective intelligence, a simplified version of the recommendation services has been implemented in the form of REST API
The service quality analysis component, which is followed by data aggregation and text mining components, practically deals with the lack of domain-specific knowledge, which is already known as a bottleneck of existing situation-aware systems
Summary
With the development of networks and the spread of smart devices, people are living in an age of flood of information [1]. In terms of people related information, the analysis can go back in time by exploring available archives In this line of context, constructing a situation-awareness supporting framework by fully exploiting the power of the collective intelligence obtained from the Web is necessary to best meet user’s needs; it aggregates raw data from the Web, extracts relevant information, converts them as a reusable format, and analyzes them according to user requests. As an effort to realize the situation-awareness supporting framework, we are focusing on how to utilize collective intelligence existing in online communities in aspects of service-specific domain knowledge To this end, we first adopt Service Quality Model for Hospitals (SQM-H), which is used for knowledge extraction, analysis, and retrieval. We present a prototype implementation for hospital recommendations that are based on the data model and the constructed knowledge, and discuss lessons learned from the implementation, while directions of our current research conclude the article
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