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Titlebook: Intelligent Information Processing X; 11th IFIP TC 12 Inte Zhongzhi Shi,Sunil Vadera,Elizabeth Chang Conference proceedings 2020 IFIP Inter

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發(fā)表于 2025-3-21 18:08:18 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Information Processing X
副標(biāo)題11th IFIP TC 12 Inte
編輯Zhongzhi Shi,Sunil Vadera,Elizabeth Chang
視頻videohttp://file.papertrans.cn/470/469714/469714.mp4
叢書名稱IFIP Advances in Information and Communication Technology
圖書封面Titlebook: Intelligent Information Processing X; 11th IFIP TC 12 Inte Zhongzhi Shi,Sunil Vadera,Elizabeth Chang Conference proceedings 2020 IFIP Inter
描述.This book constitutes the refereed proceedings of the 11th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2020, held in Hangzhou, China, in July 2020...The 24 full papers and 5 short papers presented were carefully reviewed and selected from 36 submissions. They are organized in topical sections on machine learning; multi-agent system; recommendation system; social computing; brain computer integration; pattern recognition; and computer vision and image understanding..
出版日期Conference proceedings 2020
關(guān)鍵詞artificial intelligence; clustering algorithms; computer networks; computer systems; computer vision; dat
版次1
doihttps://doi.org/10.1007/978-3-030-46931-3
isbn_softcover978-3-030-46933-7
isbn_ebook978-3-030-46931-3Series ISSN 1868-4238 Series E-ISSN 1868-422X
issn_series 1868-4238
copyrightIFIP International Federation for Information Processing 2020
The information of publication is updating

書目名稱Intelligent Information Processing X影響因子(影響力)




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書目名稱Intelligent Information Processing X網(wǎng)絡(luò)公開度學(xué)科排名




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Large-Scale Spectral Clustering with Stochastic Nystr?m Approximationensure the accurate approximation, a sufficient number of samples are needed. In very large datasets, the internal singular value decomposition (SVD) of Nystr?m will also spend a large amount of calculation and almost impossible. To solve this problem, this paper proposes a large-scale spectral clus
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Feature Selection Algorithm Based on Multi Strategy Grey Wolf Optimizer be improved by selecting the best feature subset. The classical feature selection technology has some limitations, and heuristic optimization algorithm for feature selection is an alternative method to solve these limitations and find the optimal solution. In this paper, we proposed a Multi Strateg
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Multi-label Classification of Short Text Based on Similarity Graph and Restart Random Walk Models created by using data and labels as the node, and the weights on the edges are calculated through an external knowledge, so the initial matching degree of between the sample and the label set is obtained. After that, we build a label dependency graph with labels as vertices, and using the previous
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The Conjugate Entangled Manifold of Space–Time Induced by the Law of Unity of Contradiction “.” of u and v are transmitted, respectively, from the initial time . , at different speeds . and ., and is meeting at the contradiction point .and .. Because the coordinate of contradiction point can be noted by . and . in two space time Complex Coordinates Systems which origins are . and ., respe
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Similarity Evaluation with Wikipedia Featuresween words or concepts. However, some existing Wikipedia-based SS methods either rely on a single feature or do not incorporate the underlying statistics of different features. We propose novel vector representations of Wikipedia concepts by integrating their multiple semantic features. We utilize t
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