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| 1 | Construction of an ontology-based nursing knowledge system显示文摘This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques,digital publishing technologies, and new media concepts to comprehensively integrate and deepen nursing knowledge and to aggregate sources of knowledge in specialized technical fields. This study applies all forms of media and transmission channels, such as personal computers and mobile devices, to establish a knowledge-transmission system that provides knowledge services such as knowledge search, update retrieval, evaluation, questions and answers(Q&As), online viewing, information subscription, expert services, push notifications, review forums, and online learning. In doing so, this study creates an authoritative and foundational knowledge service engine for the nursing field, which provides convenient, flexible, and comprehensive knowledge services to members of the nursing industry in a digital format. | Shi-Fan Han Rui-Fang Zhu Jia Xue Qi Yu Yan-Bing Su Xiu-Juan Wang | 2018 | Frontiers of Nursing2018，5，4： | 2 |
| 2 | Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics显示文摘Computational techniques have been adopted in medi-cal and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from origi- nal data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. | J Harold Pardue William T Gerthoffer | 2012 | World Journal of Biological Chemistry2012，3，2： | 2 |
| 3 | Meta-path-based outlier detection in heterogeneous information network显示文摘Mining outliers in heterogeneous networks is crucial to many applications,but challenges abound.In this paper,we focus on identifying meta-path-based outliers in heterogeneous information network(HIN),and calculate the similarity between different types of objects.We propose a meta-path-based outlier detection method(MPOutliers)in heterogeneous information network to deal with problems in one go under a unified framework.MPOutliers calculates the heterogeneous reachable probability by combining different types of objects and their relationships.It discovers the semantic information among nodes in heterogeneous networks,instead of only considering the network structure.It also computes the closeness degree between nodes with the same type,which extends the whole heterogeneous network.Moreover,each node is assigned with a reliable weighting to measure its authority degree.Substantial experiments on two real datasets(AMiner and Movies dataset)show that our proposed method is very effective and efficient for outlier detection. | Lu LIU Shang WANG | 2020 | Frontiers of Computer Science2020，14，2： | 1 |
| 4 | Word-Representation-Based Method for Extracting Organizational Events from Online Media显示文摘Online social media exhibit massive organizational event relevant messages, and the well categorized event information can be useful in many real-world applications. In this paper, we propose a research framework to extract high quality event information from massive online media data. The main contributions lie in two aspects: First, we present an event-extraction and event-categorization system for online media data; second, we present a novel approach for both discovering important event categories and classifying extracted events based on word representation and clustering model. Experimental results with real dataset show that the proposed framework is effective to extract high quality event information. | Jun-Qiang Zhang Xiong-Wen Deng Yu Qian | 2017 | Journal of Electronic Science and Technology2017，15，4： | 1 |
| 5 | Steps and Tools of Text Mining in Biomedical Field显示文摘The steps of text mining in biomedical field and the methods used in its each step were described with stress laid on the tools used in each step of text mining in order to promote text mining in biomedical field. | Stamatios Ramkumar Rohit Marriwala | 2018 | Biomed Communication2018，2，2： | 0 |
| 6 | Text Mining Based on the Korean Word Segmentation System in the Context of Big Data显示文摘Text mining is a text data analysis,found that the relationship between concepts and underlying concepts from unstructured text,it is extracted from large text database has not yet been realized patterns or associations,some information retrieval and text processing system can find the relationship between words and paragraphs.This article first describes the data sources and a brief introduction to the related platforms and functional components.Secondly,it explains the Chinese word segmentation and the Korean word segmentation system.At last,it takes the news,documents and materials of the Korean Peninsula as well as the various public opinion data on the network as the basic data for the research.The examples of word frequency graph and word cloud graph is carried out to show the results of text mining through Chinese word segmentation system and Korean word segmentation system. | Yongmin Quan Na Niu Hongyi Li Zhezhi Jin | 2018 | 信息工程期刊(中英文版)2018，8，1： | 0 |
| 7 | Design and Implementation of Chinese Historical Text Mining System Based on Culturomics显示文摘Culturomics and Chinese text mining methods are of great significance for analyzing the development and evolution of Chinese history and culture. To help researchers analyze a large number of Chinese historical text data, a Chinese historical text mining system based on cultruomics is designed, which includes text data processing and analyzing subsystem, text data visualizing subsystem, and text data clustering and retrieval subsystem. First of all, our system preprocesses the text data, then visualizes the text data with the frequency of words line chart and word cloud, at last selects the text data through clustering and retrieval methods. It further supports researchers to discover knowledge from a large number of historical text data. We demonstrate its general performance on text data of Canton Customs into our system. The result shows that our system is feasible and effective. | Lin Tang Chonghui Guo | 2016 | 国际计算机前沿大会会议论文集2016，，1： | 0 |
| 8 | US President Donald Trump’s Twitter Analysis and His Trade Policy Agenda显示文摘This paper makes a text analysis of the US President Donald Trump and his trade policy agenda at the national and international levels,followed by evidence-based statistical analyses of US trade.The results of President Trump’s twitters reveal that overall,President Donald Trump’s remarks contain his“populism”characterized by the use of easy-to-understand words as well as simple rhetoric,as shown most symbolically in the phrase“make America great again”.This is what is meant by“populism”,an important character of his administration(at the“meso”level)which exerts a large impact on the global(or“macro”)political and economic landscape.Such large-scale impacts can be generated by“micro”(individual level)remarks by President Trump.In more concrete terms,his micro(individual)speeches will influence his meso(national)level policy as well as the macro(NAFTA)level policy stance of the US.All these levels are interconnected in a sensitive way.NAFTA as a regional integration among the three nation states is actually under a significant influence from meso as well as micro interactions,and President Trump’s punitive trade stance may hit Chinese export negatively.Due consideration to the cross-hierarchical linkages is indeed a practical viewpoint when discussing the current,rather US-dominated trade deals. | Hikari Ishido Yuki Tashiro Richard Liang | 2018 | International Relations and Diplomacy2018，6，9： | 0 |
| 9 | Understanding traditional Chinese medicine via statistical learning of expert-specific Electronic Medical Records显示文摘Backgrounds Traditional Chinese medicine(TCM)has been attracting lots of attentions from various disciplines recently.However,TCM is still mysterious because of its unique philosophy and theoretical thinking.Due to the lack of high quality data,understanding TCM thoroughly faces critical challenges.In this study,we introduce the Zhou Archive,a large-scale database of expert-specific Electronic Medical Records containing information about 73,000+ visits to one TCM doctor for over 35 years.Covering the full spectrum of diagnosis-treatment model behind TCM practice,the archive provides an opportunity to understand TCM from the data-driven perspective.Methods:Processing the text data in the archive via a series of data processing steps,we transformed the semistructured EMRs in the archive to a well-structured feature table.Based on the structured feature table obtained,a series of statistical analyses are implemented to learn principles of TCM clinical practice from the archive,including correlation analysis,enrichment analysis,embedding analysis and association pattern discovery.Results:A structured feature table of 14,000+features is generated at the end of the proposed data processing procedure,with a feature codebook,a term dictionary and a term-feature map as byproducts.Statistical analysis of the feature table reveals underlying principles about the diagnosis-treatment model of TCM,helping us better understand the TDM practice from a data-driven perspective.Conclusion:Expert-specific EMRs provide opportunities to understand TCM from the data-driven perspective.Taking advantage of recent progresses on NLP for Chinese,we can process a large number of TCM EMRs efficiently to gain insights via statistical analysis. | Yang Yang Qi Li Zhaoyang Liu Fang Ye Ke Deng | 2019 | Quantitative Biology2019，7，3： | 0 |
| 10 | Survey of Sustainable Logistics Services via Text Mining显示文摘Environmental sustainability has recently become more and more of a concern in logistics service industry. Although studies on sustainable initiatives among logistics service providers (LSP) have been increasing in the extant literature, still little investigation has been performed between LSPs and shippers. The present paper aims to demonstrate award-gained sustainable logistics service initiatives implemented during the period 2006-2017 in Japan. Different with questionnaire- and interview-based studies employed in literature, we use text mining technique to explore the co-occurring links of data, i.e. connections of the practices, to present the collaborative sustainability actions carried out through providing and requiring logistics services. In contrast to the research regarding green supply chain management focused on manufacturing perspective, this study is positioned in the dual sides of consignors and logistics business operators, to depict their combined effort in achieving sustainability goals. The results of the study showed that text mining technique is useful for summarizing and presenting data in this research area. However, much remains to be learned about how to deal with the data more means-end logically for revealing more indirect associations between the data. | Fuyume Sai | 2019 | Journal of Mechanics Engineering and Automation2019，9，3： | 0 |
| 11 | A Social Stability Analysis System Based on Web Sensitive Information Mining显示文摘Researches on domestic social stability analysis mainly focus on construction of social stability theory,architecture and index,while few pay attention on quantitative analysis.In this paper,a social stability supervising framework is proposed based on sensitive Web information mining,semantic pattern matching and quantitative calculating.A sensitive information knowledge base is constructed by analyzing sensitive information about social environment,national harmonious and happy index of people’s live in natural language online news texts from Internet,and recognizing hot keywords as well as the event trends led by the keywords.A social stability index theoretic model and a quantitative calculating model are proposed to evaluate social stability quantitatively.Parameters of the calculating model are determined by employing social investigations and an iterative feedback learning method.A prototype system is built on proposed framework and experiments are conducted on six frontier provinces,e.g.,Xinjiang and Tibet.The result of an average accurate of 73.29%shows the effectiveness of the proposed model. | Wei Wang | 2015 | 国际计算机前沿大会会议论文集2015，，B12： | 0 |
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