Lei Li

Due to the different effects of the factors affecting the power communication network security situation on network security, the accuracy of security situation awareness is low. Therefore, a power communication network security situation awareness method based on LDA-RBF is proposed. The linear relationship between influencing factors is established through LDA, and the hierarchical structure model is constructed to normalize the situational awareness factors and divide the corresponding levels of different influencing indicators. RBF is used to construct security situation awareness function, and ReLU is introduced to replace tanh in RBF to improve the accuracy of perception results. The test results show that the design method has a high degree of fit between the network security situational awareness results and the actual value, and has a good application effect.

Popular online publishers produce huge amount of news articles every day, so it is important to summarize the most up-to-the-minute information to help users quickly know the progresses of their interested news events. In this paper, we develop NewsCubeSum, a novel personalized news summarization system utilizing OLAP and supervised sentence selection techniques to generate brief summaries delivering news updates in multiple dimensions (such as time, entity, and topic). An illustrative case study and experimental results on summarization performance comparisons are provided to show the effectiveness of NewsCubeSum.

The fast growth of technologies has driven the advancement of our society. It is often necessary to quickly grab the evolution of technologies in order to better understand the technology trend. The availability of huge volumes of granted patent documents provides a reasonable basis for analyzing technology evolution. In this paper, we propose a unified framework, named PatentLine, to generate a technology evolution tree for a given topic or a classification code related to granted patents. The framework integrates different types of patent information, including patent content, citations of patents, temporal relations, etc., and provides a concise yet comprehensive evolution summary. The generated summary enables a variety of patent-related analyses such as identifying relevant prior art and detecting technology gap. A case study on a collection of US patents demonstrates the efficacy of our proposed framework.

Domain ontology, as a conceptual model, provides a meaningful framework for semantic representation of textual information. In this paper, we explore the feasibility of using the ontology in solving multi-document summarization problems in the domain of disaster management. We provide an empirical study of different approaches in which the ontology has been used for summarization tasks. Extensive experiments on a collection of press releases relevant to Hurricane Wilma in 2005 demonstrate that ontology-based multi-document summarization methods outperform other baselines in terms of the summary quality.