The intelligent question answering (IQA) system can accurately capture users' search intention by understanding the natural language questions, searching relevant content efficiently from a massive knowledge-base, and returning the answer directly to the user. Since the IQA system can save inestimable time and workforce in data search and reasoning, it has received more and more attention in data science and artificial intelligence. This article introduced a domain knowledge graph using the graph database and graph computing technologies from massive heterogeneous data in electric power. It then proposed an IQA system based on the electrical power knowledge graph to extract the intent and constraints of natural interrogation based on the natural language processing (NLP) method, to construct graph data query statements via knowledge reasoning, and to complete the accurate knowledge search and analysis to provide users with an intuitive visualization. This method thoroughly combined knowledge graph and graph computing characteristics, realized high-speed multi-hop knowledge correlation reasoning analysis in tremendous knowledge. The proposed work can also provide a basis for the context-aware intelligent question and answer.
Cloud computing is featured by powerful computing capabilities. However, the resource allocation puts forward new challenges. A highly efficient resource allocation scheme is of great significance in parallel processing of cloud computing. In this paper, we propose a novel dynamic resource allocation algorithm with cooperation strategy. We first model and analyze the resource allocation problem theoretically. We introduce a heuristic information-based algorithm with the cooperation of all the computing nodes. We describe the algorithm in details; introduce the related parameters and algorithm steps. We analyze the algorithm and also evaluate its performance by simulation experiments. The experiment results indicate that our algorithm conducts resource allocation fast and effectively, achieving superior performance as well.
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