An Approach for Value as a Service Discovery on Scientific Papers Big Data

With the integration of cloud computing and big data, it is difficult for the masses to discover valuable service from big data. The understanding of historical data and streaming data is fundamental to the value discovery, and the construction of topic knowledge is essential to the understanding of big data. This paper proposes an approach for the construction of topic knowledge based on ontology meta-modeling, and the approach follows three stages: classification, clustering and integration. Furthermore, the realization of the three stages is based on support vector machine, probability computing, and ontology meta-modeling. Finally, experiments on scientific papers of service computing were conducted in order to get the recommended reviewers. The results of the experiments demonstrate the effectiveness of the approach. In conclusion, the approach provides a solution for the value discovery from big data.