Distributed Big Data Computing for Supporting Predictive Analytics of Service Requests

Abstract

In the current era of big data, huge volumes of valuable data can be easily generated and collected at a rapid velocity from a wide variety of rich data sources. In recent years, the initiates of open data also led to the willingness of many government, researchers, and organizations to share their data and make them publicly accessible. An example of open big data is service request data. Analyzing these open big data can be for social good. For instance, by analyzing and mining data on non-emergency city service requests, the city could get an insight about its residents’ demand for services. By taking appropriate actions (e.g., adding more staff and/or services, providing more information regarding city services) could enhance the living condition of city residents. In this paper, we present a distributed big data mining system to analyze and mine big data on these non-emergency city service requests. Evaluation on an open big data from a North American city shows the effectiveness and practicality of our distributed big data system in mining these requests for city services and in supporting predictive analytics.