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Titlebook: Data Science; 4th International Co Qinglei Zhou,Qiguang Miao,Zeguang Lu Conference proceedings 2018 Springer Nature Singapore Pte Ltd. 2018

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发表于 2025-3-21 18:46:14 | 显示全部楼层 |阅读模式
书目名称Data Science
副标题4th International Co
编辑Qinglei Zhou,Qiguang Miao,Zeguang Lu
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Data Science; 4th International Co Qinglei Zhou,Qiguang Miao,Zeguang Lu Conference proceedings 2018 Springer Nature Singapore Pte Ltd. 2018
描述This two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. .The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven busi
出版日期Conference proceedings 2018
关键词artificial intelligence; cloud computing; clustering algorithms; computer crime; data mining; data securi
版次1
doihttps://doi.org/10.1007/978-981-13-2206-8
isbn_softcover978-981-13-2205-1
isbn_ebook978-981-13-2206-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2018
The information of publication is updating

书目名称Data Science影响因子(影响力)




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书目名称Data Science网络公开度学科排名




书目名称Data Science被引频次




书目名称Data Science被引频次学科排名




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书目名称Data Science年度引用学科排名




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Stylianos Sergis,Demetrios G. Sampsonaction based on syntactic parsing is used to get keywords of each evidence and fact. Text similarity measure based on Word2vec and keyword overlap ratio calculation is used to get the connection point of evidence chain. Predefined weight of different kinds of evidence can be used to measure the impo
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Jim Allen,Yuki Inenaga,Keiichi Yoshimotod, and proves the validity of these two methods in the sentiment analysis task. At the same time, the emotion adjustment method based on skip-gram model is more effective than the method based on semantic similarity.
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The Competency of Definitions of Competencyan improve the accuracy rate by about 47% and 8% respectively. This method gets some new terms that are not contained in the thesaurus. It verifies the effectiveness of machine learning in term extraction.
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https://doi.org/10.1007/978-94-007-5386-0ults show that the accuracy rate, recall rate and F value that we got in an unaddressed artificial features condition are 98.81%, 90.70% and 91.57% respectively which is better than the results we got by using the method of BILSTM+CRF and conditional random field (CRF).
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Richard LeSar,Alan Bishop,Robert Heffnerh. Then, we obtained attraction vectors and user vectors fused with feature attributes of attractions and spatial-temporal semantics. At last we calculate the correlation between tourists and attractions with cosine similarity to give a list of recommendations. Our evaluation on real travel spatial-
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Automatic Generation of Multiple-Choice Items for Prepositions Based on Word2vec,
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