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22nd International Conference on Intelligent User Interfaces, IUI 2017

作者： Chen, Jun Jacucci, Giulio Chen, Yueguo Ruotsalo, Tuukka School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Helsinki Institute for Information Technology HIIT Department of Computer Science University of Helsinki Finland

ISBN: (纸本)9781450348935

Entity search and exploration can enrich search user interfaces by presenting relevant information instantly and offering relevant exploration pointers to users. Previous research has demonstrated that large knowledge Graphs allow exploitation and recommendation of explicit links between the entities and other information to improve information access and ranking. However, less attention has been devoted to user interfaces for effectively presenting results, recommending related entities and explaining relations between entities. We introduce a system called SEED which is designed to support entity search and exploration in large knowledge Graphs. We demonstrate SEED using a dataset of hundreds of thousands of movie related entities from the DBpedia knowledge Graph. The system utilizes a graph embedding model for ranking entities and their relations, recommending related entities, and explaining their interrelations. Copyright is held by the author/owner(s).

关键词： knowledge graph

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An integration management system for managing business continuity, records and knowledge

An integration management system for managing business conti...

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International Forum on Information Technology and Applications

作者： An, Xiaomi Chao, Lemen Ye, Liuqi Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing 100872 China Economic Management School Beijing Institute of Petrol-chemical Technology Beijing 102617 China

ISBN: (纸本)9780769541150

Developing an integration management system for business continuity, records and knowledge (IMS of BRK) is beneficial to the collaboration, optimization and innovation of business continuity management system (BCMS), records management system (RMS) and knowledge management system (KMS) for organization. Comprehensive research and development requirements along with a cogent framework, however, have not been proposed for integrating three of them, which were proposed independently. Based on situational analysis of cross boundaries integration feasibilities in terms of common understandings, general principles and best practice frameworks from relevant national and international standards, this paper proposes integration thinking to combine the advantages of the three paradigms to sustainable competitive advantages;supported by international best practices, the authors propose an integration route covering five levels of integration framework, two integration approaches and three integration controls for dynamic accumulation, sharing and exchange of evidence, memory and knowledge in digital world and global competition. © 2010 IEEE.

关键词： knowledge management

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A novel hybrid butterfly optimization algorithm for feature selection with sine cosine velocity in the high-dimensional classification data

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Journal of Intelligent and Fuzzy Systems 2024年第5-6期47卷 369-391页

作者： Zhang, Li Chen, Xiaobo Key Laboratory of Data Science and Intelligence Education Hainan Normal University Ministry of Education Haikou Hainan China School of Computer Engineering Jiangsu University of Technology Changzhou Jiangsu China Changzhou City Center Branch People's Bank of China Changzhou Jiangsu China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

Aiming at the shortcomings of the traditional butterfly optimization algorithm in solving the high-dimensional classification feature selection problem, which has low convergence and is prone to fall into local optimal solutions, a new hybrid butterfly optimization algorithm is proposed, i.e., HBOA-SCV (A novel hybrid butterfly optimization algorithm with sine cosine velocity). The algorithm is applied to solve a high-dimensional classification feature selection problem. Firstly, the algorithm's global exploration and local exploitation ability can be dynamically balanced by introducing inertia weight coefficients w based on multiple learning strategies. Secondly, using the updated speed position formula of the sine-cosine acceleration strategy, individual butterflies' autonomous search ability and convergence speed can be further improved. Finally, according to the fitness value of each butterfly individual, the moving step length and direction of the butterfly individual are automatically adjusted better to fit the actual search process of the butterfly individual, increase the search ability in the global range, and avoid the algorithm from falling into the local optimum. To verify the algorithm's effectiveness, 18 high-dimensional classification numbers are selected to carry out simulation and comparison experiments between HBOA-SCV and traditional BOA algorithm, five improved BOA algorithms and other comparative algorithms for high-dimensional classification data successively. The experimental results show that the average fitness value and classification accuracy of the HBOA-SCV algorithm are better than the comparison algorithm, thus verifying the superiority of the HBOA-SCV algorithm. © 2024 - IOS Press. All rights reserved.

关键词： Optimization algorithms

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Clustering XML search results based on content and structure similarity

Clustering XML search results based on content and structure...

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Min-Juan, Zhong Chang-Xuan, Wan De-Xi, Liu Xian-Pei, Jiao School of Information and Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

Clustering XML search results is an effective way to improve performance. However, the key problem is how to measure similarity between XML documents. In this paper, we propose a semantic similarity measure method combining content with structure, in which a variety of XML document features, including term element frequency, term inverse element frequency, semantic weight of tag label and level information of the term, are analyzed and applied for computing the similarity between XML documents. In addition, two new performance evaluation methodology, namely Cluster Ratio Relevant and Docu Ratio Relevant, for clustering quality are introduced motivated by the observations of relevant documents distribution and the fact that collection has no classification information. Experiment results show that proposed similarity method(CAS measure)outperforms traditional document clustering(CO measure) in Cluster Ratio Relevant and Docu Ratio Relevant and produces better clustering quality. © 2011 IEEE.

关键词： XML

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Sentimental analysis of web financial reviews opportunities and challenges 6

Sentimental analysis of web financial reviews opportunities ...

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6th International Conference on knowledge Discovery and Information Retrieval, KDIR 2014

作者： Wan, Changxuan Jiang, Tengjiao Liu, Dexi Liao, Guoqiong School of Information and Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9789897580482

Web financial reviews are real-time, comprehensive and authentic. The construction and quantification of Web financial indexes based on Web financial reviews is of great significance for the financial early warning for enterprises. Comparing with product reviews and news commentaries, in Web financial reviews, the opinion targets have more diverse compositions, the frequencies of opinion targets' occurrence vary greatly, and the sentiment words' have more diverse parts of speech. These characteristics make the extraction of opinion targets, the construction of Web financial indexes, and opinion targets-based sentimental analysis all more complicated, posing new challenges to natural language processing. Copyright © 2014 SCITEPRESS - Science and Technology Publications All rights reserved.

关键词： Sentiment analysis

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Research on XML element search results clustering

Research on XML element search results clustering

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6th International Conference on Management of e-Commerce and e-Government, ICMeCG 2012

作者： Zhong, Min-Juan Wan, Chang-Xuan Liu, De-Xi Jiao, Xian-Pei School of Information Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9781467329439

Clustering XML search results is an effective way to improve performance. However, the key problem is how to measure similarity between XML documents. This paper studies XML search results clustering based on element granularity and proposes one similarity measurement method. The method firstly uses latent semantic indexing technology(LSI) to obtain term semantics and then combines the XML element node content and semantic structure properties(CASS). To evaluate clustering performance, two new performance evaluation methodologies, namely R-ClusterRatio and R-DocuRatio are introduced. It is motivated by the observations of relevant documents distribution and the fact that the experiment data collection, IEEE CS corpus, do not provide classification information. Experiment results show that proposed similarity method combining term semantics with content and structure semantics integration(LSI-CASS) is feasible, and it produces better clustering quality than LSI-CAS. © 2012 IEEE.

关键词： Semantics

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Research on Automatic Proofreading Method of Sensitive Information in Content Security 2

Research on Automatic Proofreading Method of Sensitive Infor...

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2nd International Symposium on Application of Materials Science and Energy Materials, SAMSE 2018

作者： Gong, Yonggang Li, Yuying Lian, Xiaoqin Fu, Junying School of Computer and Information Engineering Beijing Technology and Business University Beijing Key Laboratory of Food Safety Big Data Technology Beijing China

Aiming at the problem of automatic proofreading of sensitive information in mass text content, an automatic proofreading method based on the combination of rule and SVM (Support Vector Machine) is proposed. To classify sensitive information based on important sensitive information provided in the "Newly Prohibited Texts and Cautions in Xinhua News Reports"(newest revision) and related central and online *** to the different categories, the paper constructs the classification processing rule base, designs the corresponding rules automatic Processing algorithm, and realizes the sensitive information automatic proofreading, At the same time, using the SVM model to analyze the result of the rule processing with emotion, which greatly reduces the false alarm rate. The test result shows that the recall rate of method is 89.98%, the accuracy rate is 98.31%, and 100, 000 + text content is processed per second, which solves the key difficult problems in the practical engineering application. © Published under licence by IOP Publishing Ltd.

关键词： Support vector machines

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An effective XML identifying feedback documents method based on two-stage ranking model for pseudo-relevance feedback

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2013 3rd International Symposium on Chemical engineering and Material Properties, ISCEMP 2013

作者： Zhong, Min Juan School of Information Technology Jiangxi University of Finance and Economics Nanchang China JiangXi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783037858363

Although pseudo relevant feedback is an effective query expansion method, query drift away from the topic has been occurred frequently. Therefore, the first important problem is how to identify relevant documents in the top retrieved set and form the good feedback source. In this paper, an effective XML identifying feedback documents method is proposed, in which a two-stage ranking model is presented and the relevant XML documents are found. The experiment results show that the proposed method is reasonable and the quality of feedback source is ensured. © (2013) Trans Tech Publications, Switzerland.

关键词： XML

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Swot analysis of Chinese rural information society policies

Swot analysis of Chinese rural information society policies

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2nd International Conference on Mechatronics and Industrial Informatics, ICMII 2014

作者： Zhou, Ping School of Information Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783038351764

This paper presents an analysis of strengths, weaknesses, opportunities, and threats (SWOT) for Chinese rural information society development (CRISD) policies in terms of its missions and strategies. After briefly describing the institutional and information society development contexts, the paper draws on literature reviews and questionnaires survey to list of SWOT factors for CRISD. These findings could be used to help adjust the next step work to support decision making for rural information society construction and to provide a valuable reference for other investors who are planning to invest in information society programs in China's rural regions. This article presents valuable missions and strategic goals through the SWOT analysis for realizing information society development in Chinese rural areas. © (2014) Trans Tech Publications, Switzerland.

关键词： Rural areas

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MatchPrompt: Prompt-based Open Relation Extraction with Semantic Consistency Guided Clustering

MatchPrompt: Prompt-based Open Relation Extraction with Sema...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Wang, Jiaxin Zhang, Lingling Liu, Jun Liang, Xi Zhong, Yujie Wu, Yaqiang Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering School of Computer Science and Technology Xi'an Jiaotong University China National Engineering Lab for Big Data Analytics Xi'an Jiaotong University China Lenovo Research Beijing China

Relation clustering is a general approach for open relation extraction (OpenRE). Current methods have two major problems. One is that their good performance relies on large amounts of labeled and pre-defined relational instances for pre-training, which are costly to acquire in reality. The other is that they only focus on learning a high-dimensional metric space to measure the similarity of novel relations and ignore the specific relational representations of clusters. In this work, we propose a new prompt-based framework named MatchPrompt, which can realize OpenRE with efficient knowledge transfer from only a few predefined relational instances as well as mine the specific meanings for cluster interpretability. To our best knowledge, we are the first to introduce a prompt-based framework for unlabeled clustering. Experimental results on different datasets show that MatchPrompt achieves the new SOTA results for OpenRE. © 2022 Association for Computational Linguistics.

关键词： Extraction

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