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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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A method for measuring journal discriminative capacity and its application in WOS 15th

A method for measuring journal discriminative capacity and i...

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15th International Conference on Sustainable Digital Communities, iConference 2020

作者： Wang, Hao Zhang, Baolong Deng, Sanhong Su, Xinning School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030436865

Journal discriminative capacity refers to the degree of difference between the journals in research subjects, and is of great significance for detecting the level of journal differentiation. Current research on journal discrepancies is predominantly focused on the quantitative analysis of journal content, and rarely measures the degree of journal difference. To address this lapse in research, a method from the perspective of difference is proposed in this paper to quantitatively measure and analyze the discriminative capacity of journals. Using the bibliographic of Science Citation Index (SCI), Social Science Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI) journals from 2015–2017 as the data source, the contents differences of 23 Library and Information Science (LIS) journals are analyzed through hierarchical clustering and journal discriminative capacity (JDC) measurement. The discriminative capacity of disciplines is then calculated and combined with multidimensional scaling analysis to detect the difference characteristics of journals in ten disciplines, and the mean JDC is used to explore the overall differences of disciplines. Results show that the discriminative capacity of LIS journals is obviously stratified, the journals of library science are the most discriminating, and the journals of evaluation and review are the weakest. In addition, the journals of different disciplines have distinct disciplinary characteristics, with the discriminative capacity of SCI journals as the most notable, followed by SSCI journals, and with A&HCI journals displaying the weakest discriminative capacity. © Springer Nature Switzerland AG 2020.

关键词： Digital libraries

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A Semantic Framework for Chinese Historical Events Based on Linked data and knowledge Graph 16th

A Semantic Framework for Chinese Historical Events Based on ...

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16th International Conference on Diversity, Divergence, Dialogue, iConference 2021

作者： Wang, Hao Li, Yueyan Deng, Sanhong School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030712914

In the era of big data, data redundancy has become an obstacle to deep reading. The objective of linked data as a new data organization model is to transform data into structured data following unified standards. The lack of Chinese conceptual terms has seriously hindered the semantization and standardization of Chinese domain ontology. Taking Chinese historical events as an example, ontology technology is used in this paper to standardize the definition of concepts and semantic relations in domain knowledge. Moreover, concepts from text resources are extracted through a deep learning algorithm Bi-LSTM-CRFs and combined with an external knowledge base to realize the fusion of related data within various data sets. Ultimately, the knowledge ontology of historical events is displayed in the way of a knowledge graph to further explore the practical application. The results show that the accuracy of the terms extraction of historical events is about 80% indicating the good recognition performance and portability of the model. © 2021, Springer Nature Switzerland AG.

关键词： Linked data

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A Metric Approach to Hot Topics in Biomedicine via keyword Co-occurrence

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Journal of data and Information Science 2019年第4期4卷 13-25页

作者： Jane H.Qin Jean J.Wang Fred Y.Ye Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China International Joint Informatics Laboratory(IJIL) Nanjing University-University of IllinoisNanjing-ChampaignChina-USA

Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic ***/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric ***:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each *** limitations:All analyses use keywords,without any other *** implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical ***/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.

关键词： keyword co-occurrence Network analysis Information visualization Biomedicine Hot topics CRISPR-Cas iPS cell Synthetic biology

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Short Text Topic Modeling Techniques, Applications, and Performance: A Survey

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IEEE Transactions on knowledge and data engineering 2022年第3期34卷 1427-1445页

作者： Qiang, Jipeng Qian, Zhenyu Li, Yun Yuan, Yunhao Wu, Xindong Department of Computer Science Yangzhou University Jiangsu225009 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Hefei Anhui230026 China Mininglamp Academy of Sciences Minininglamp Beijing China

Analyzing short texts infers discriminative and coherent latent topics that is a critical and fundamental task since many real-world applications require semantic understanding of short texts. Traditional long text topic modeling algorithms (e.g., PLSA and LDA) based on word co-occurrences cannot solve this problem very well since only very limited word co-occurrence information is available in short texts. Therefore, short text topic modeling has already attracted much attention from the machine learning research community in recent years, which aims at overcoming the problem of sparseness in short texts. In this survey, we conduct a comprehensive review of various short text topic modeling techniques proposed in the literature. We present three categories of methods based on Dirichlet multinomial mixture, global word co-occurrences, and self-aggregation, with example of representative approaches in each category and analysis of their performance on various tasks. We develop the first comprehensive open-source library, called STTM, for use in Java that integrates all surveyed algorithms within a unified interface, benchmark datasets, to facilitate the expansion of new methods in this research field. Finally, we evaluate these state-of-the-art methods on many real-world datasets and compare their performance against one another and versus long text topic modeling algorithm. © 2020 IEEE.

关键词： Surveys

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Towards multi-target search of semantic association 6th

Towards multi-target search of semantic association

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6th Joint International Conference on Semantic Technology, JIST 2016

作者： Zhang, Xiang Lv, Yulian School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Data Engineering and Knowledge Services Nanjing University Nanjing China Southeast University Suzhou China

ISBN: (纸本)9783319501116

Semantic association represents group relationship among objects in linked data. Searching semantic associations is complicated, which involves the search of multiple objects and the search of their group relationships simultaneously. In this paper, we propose this kind of search as a multi-target search, and we compare it to traditional search tasks, which we classify as single-target search. A novel search model is introduced, and the notion of virtual document is used to extract linguistic information of semantic associations. Multi-target search is finally fulfilled by a PageRank-like ranking scheme and a top-K selection policy considering object affinity. Experiments show that our approach is effective in improving retrieval precision on semantic associations. © Springer International Publishing AG 2016.

关键词： Linked data

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Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods

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Computer Modeling in engineering & Sciences 2021年第10期129卷 31-45页

作者： Lejun Gong Xingxing Zhang Li Zhang Zhihong Gao Jiangsu Key Laboratory of Big Data Security&Intelligent Processing School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210046China Smart Health Big Data Analysis and Location Services Engineering Laboratory of Jiangsu Province Nanjing210046China College of Computer Science and Technology Nanjing Forestry UniversityNanjing210037China Zhejiang Engineering Research Center of Intelligent Medicine Wenzhou325035China

Novel coronavirus disease 2019(COVID-19)is an ongoing health *** studies are related to ***,its molecular mechanism remains *** rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational *** paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine *** method obtains seed genes based on prior *** genes are mined from biomedical *** candidate genes are scored by machine learning based on the similarities measured between the seed and candidate ***,the results of the scores are used to perform functional enrichment analyses,including KEGG,interaction network,and Gene Ontology,for exploring the molecular mechanism of *** results show that the method is promising for mining genotype information to explore the molecular mechanism related to COVID-19.

关键词： COVID-19 SARS-CoV-2 computational method bioinformatics genotype machine learning

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Research on Influencing Factors of College Students' Intention of Online Health Information Behavior Based on Social Cognitive Theory 2

Research on Influencing Factors of College Students' Intenti...

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2019 2nd International Conference on Advanced Algorithms and Control engineering, ICAACE 2019

作者： Kong, Jia Deng, Sanhong Zhang, Yue School of Information Management Nanjing University Nanjing210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing210023 China

Based on the Social Cognition Theory, we constructed the influencing factors model of college students' intention of online health information behavior from three levels of individual, society and information systems, which was analyzed by using the PLS-SEM. Research shows that self-efficacy, information service quality, social support, information literacy and information quality significantly influence college students' intention of online health information behavior. However, the influence of perceived risk and information system quality is not significant. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Information systems

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RETRACTED ARTICLE: Studies of knowledge management methods from literature

RETRACTED ARTICLE: Studies of knowledge management methods f...

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作者： Zhang, Jing Ye, Liuqi Business School of Hohai University Nanjing Jiangsu 210098 China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing 100872 China

ISBN: (纸本)9781424469291

knowledge management methods reflect ways to undertake knowledge management objectives and actions taken for implementation. However, little has been written on the topic. The paper summarizes main topics of knowledge management methods from literature, including research contents, management methods, main types, objects involved, study domains, perspectives, objectives and tasks, school and achieving channels, developing trends and knowledge management methodology and etc. © 2010 IEEE.

关键词： knowledge management

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An Empirical Study on the Tourism Image of Nanjing from the Perspective of International Students 7th

An Empirical Study on the Tourism Image of Nanjing from the ...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Han, Pu Zhang, Mingtao Yao, Mingxiu Hui, Zhenrong Chen, Meitong School of Management Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030786175

International students are a special group in Chinese cities, and their tourism image perception has important research significance for urban tourism construction. Based on the destination tourism image model proposed by Baloglu and McCleary, the tourism image of Nanjing is divided into three aspects: cognitive image, emotional image and overall image. Aiming at the international student group in Nanjing, the questionnaire survey was used to obtain the perception data of the group’s tourism image in Nanjing with SPSS. The empirical research on the tourism image of Nanjing was carried out from three aspects: tourism image perception factor, overall image perception and representative attractions. The study found that in the structured part of the dimension, international students are most satisfied with "urban environment" and least concerned about "attractions". Through the single factor measurement, the most satisfied one is the rich historical and cultural heritage, and the most dissatisfied one is the crowded urban environment. In the unstructured part of the international students on Nanjing tourism image, the overall satisfaction is high, in which the destination image perception of the "delicious food" is the best. In the perception of urban tourism image, the perception of "a beautiful city" is the best. The analysis of the characteristics of social population structure shows obvious individualized difference. Boys tend to Zhongshan mausoleum, and girls are more inclined to Confucius Temple Qinhuai scenery belt. © 2021, Springer Nature Switzerland AG.

关键词： Surveys

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