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检索条件"任意字段=5th International Conference on Data Mining and Big Data, DMBD 2020"

共 1548 条记录，以下是51-60 订阅

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Research on Personalized Service Strategy of University Library Based on big data mining System 5

Research on Personalized Service Strategy of University Libr...

引用

5th international conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Sun, Yanjun Sun, Jianwei Wu, Wenshuang Du, Qiang Zhao, Haiyan Liu, Juanjuan Tianjin Tianshi Coll Sch Informat Sci & Engn Tianjin 301700 Peoples R China Tianjin Tianshi Coll Lib Tianjin 301700 Peoples R China

ISBN: (数字)9781728182780

ISBN: (纸本)9781728182780

In order to improve the level and efficiency of personalized service of university library, and to meet the personalized needs of college teachers and students for borrowing books, this paper puts forward a novel personalized service strategy of university library based on big data mining system. this strategy is based on big data mining technology, and comprehensively adopts high and new technologies such as association data analysis, clustering data analysis, classification data analysis and so on. the research shows that this strategy can not only really improve the level and efficiency of personalized service of university library, but also meet the personalized needs of college teachers and students to borrow books to a certain extent.

关键词： big data mining system University library Personalized service

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A Survey of Clustering Techniques for big data Analysis 5

A Survey of Clustering Techniques for Big Data Analysis

引用

5th international conference on Confluence - the Next Generation Information Technology Summit (Confluence)

作者： Arora, Saurabh Chana, Inderveer Thapar Univ Dept Comp Sci & Engn Patiala Punjab India

ISBN: (纸本)9781479942367

With the beginning of new era data has grown rapidly not only in size but also in variety. there is a difficulty in analyzing such big data. data mining is the technique in which useful information and hidden relationship among data is extracted. the traditional data mining approaches could not be directly implanted on big data as it faces difficulties to analyze big data. Clustering is one of the major techniques used for data mining in which mining is performed by finding out clusters having similar group of data. In this paper we have discussed some of the current big data mining clustering techniques. Comprehensive analysis of these techniques is carried out and appropriate clustering algorithm is provided.

关键词： big data Clustering Techniques data mining

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Knowledge discovery and framework for purchase behavior analysis in mobile gaming applications 14

Knowledge discovery and framework for purchase behavior anal...

引用

14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and 5th IADIS international conference big data Analytics, data mining and Computational Intelligence 2020, bigDaCI 2020 and 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

作者： Jansevskis, Martins Osis, Kaspars Faculty of Engineering Vidzeme University of Applied Sciences Valmiera Latvia

ISBN: (纸本)9789898704214

the gaming industry is a fast expanding industry with a large global market and is projected to hit $300 billion by 2025. the total number of players in 2019 was projected to hit 2.4 billion (Taylor, 2019). Knowledge discovery is achieved by collecting and analyzing data from within the gaming applications. the data collected is used to understand players, gain insights and to improve products for the gaming community based on feedback and user interaction. And as a result, obtained knowledge contributes to monetization in a way that is especially interesting in the e-sports and streaming space. Machine learning is one of the technologies that can assist in knowledge discovery as it provides potential to obtain insights into previously overlooked data. this paper provides insight in a work of how machine learning algorithms are applied to gain behavior understanding whithin mobile gaming applications in a way compliant with European General data Protection Regulation (GDPR). the paper is a part of a larger research work and contributes to the domain of knowledge discovery within in-app purchase behavior data and serves as a step towards further research in this area. © Proceedings of the 14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS international conference big data Analytics, data mining and Computational Intelligence 2020, bigDaCI 2020 and Proceedings of the 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： data mining

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Approaching the (big) data Science Engineering Process 5

Approaching the (Big) Data Science Engineering Process

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5th international conference on Internet of things, big data and Security (IoTBDS)

作者： Volk, Matthias Staegemann, Daniel Bosse, Sascha Haeusler, Robert Turowski, Klaus Otto von Guericke Univ Fac Comp Sci Magdeburg Res & Competence Cluster Very Large Bus Magdeburg Germany

ISBN: (纸本)9789897584268

For many years now, researchers as well as practitioners are harnessing well-known data mining processes, such as the CRISP-DM or KDD, to realize their data analytics projects. In times of big data and data science, at which not only the volume, variety and velocity of the data increases, but also the complexity to process, store and manage them, conventional solutions are often not sufficient and even more sophisticated systems are needed. To overcome this situation, in this positioning paper the (big) data science engineering process is introduced to provide a guideline for the realization of data-intensive systems. For this purpose, using the design science research methodology, existing theory and current literature from relevant subdomains are contextualized, discussed and adapted.

关键词： big data data Science Engineering Process

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On efficiently creating temporally biased samples over data streams: Beyond memoryless functions 14

On efficiently creating temporally biased samples over data ...

引用

作者： Lagogiannis, George Makris, Christos Department of Agricultural Economics and Rural Development Agricultural University of Athens Iera Odos 75 Athens11855 Greece Department of Computer Engineering and Informatics University of Patras Patras26504 Greece

ISBN: (纸本)9789898704214

When creating a sample over a data stream, we sometimes need to give a priority to the recent past, over the distant one. this can be achieved if the probability of each stream element to exist in the sample decays as time passes, according to a bias-function. In order to obtain such a sample, one has to access some elements of the sample when a stream element arrives. For the exponential bias-function, according to which the probability of a sample-element to be deleted at each time-point, is the same for all sample elements, the number of needed accesses is O(1). For any other bias-function, one needs to access O(n) elements per incoming stream element, where n is the sample-size. In this paper we present an algorithm that achieves O(1) amortized accesses for any bias-function such that at each time-point, the probability of a sample-element to be deleted increases over time. © Proceedings of the 14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS international conference big data Analytics, data mining and Computational Intelligence 2020, bigDaCI 2020 and Proceedings of the 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： data mining

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Framework for data mining of big data Using Probabilistic Grammars 5

Framework for Data Mining of Big Data Using Probabilistic Gr...

引用

5th international conference on e-Learning (econf)

作者： Algwaiz, Aljoharah Ammar, Reda Rajasekaran, Sanguthevar Univ Connecticut Dept Comp Sci & Engn Storrs CT 06269 USA

ISBN: (纸本)9781467394314

Most commonly used and researched data mining approaches use neural and statistical methods to extract information for large data sources. this paper proposes a framework for a novel approach in data mining using Probabilistic Context Free Grammar (PCFG). the framework is proposed for two distributed data structures;dependent and independent. Escherichia Coli promoter DNA sequences dataset are chosen as a case study in this paper.

关键词： big data data mining Grammar Linguistics Parsing

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the Application of data mining in Fault Location of Computer Interlocking System in Railway Signling 5

The Application of Data Mining in Fault Location of Computer...

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5th IEEE international conference on Cloud Computing and big data Analytics, ICCCBDA 2020

作者： Lujiang, Huang CASCO Signal Ltd. Shanghai China

ISBN: (纸本)9781728160245

the complex faults in computer interlocking systems require experienced technicians to locate them by filtering and analyzing a large amount of system log information. this paper, data mining algorithm is introduced to pick up the feature variables that have the most important impact on the target variable (fault state variable) from multiple feature variables, so as to narrow and locate the fault range. the effectiveness of this method is verified by the real failure case, which provides a novel method for fault location of computer interlocking system. © 2020 IEEE.

关键词： data mining

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data-driven approach for generating colormaps of scientific simulation data 14

Data-driven approach for generating colormaps of scientific ...

引用

作者： Cao, Yi Wang, Xiaohua Wang, Huawei Ai, Zhiwei Xia, Fang High Performance Computing Center Institute of Applied Physics and Computational Mathematics Beijing China CAEP Software Center for High Performance Numerical Simulation Beijing China

ISBN: (纸本)9789898704214

the colormap plays important roles in the exploration, analysis, and discovery of scientific data. datasets generated by real-world simulation applications are becoming increasingly more complex: the distribution of the variable values within the data is often extremely uneven and accompanied by high levels of data noise. the heterogeneity of these data characteristics presents rich information about physical laws as well as technical challenges for colormap of visualization. Most default colormaps are defined by linearly interpolating dataset values and cannot be adapted to convey the physical meaning behind complicated data. In this paper, we introduce a data-driven approach for generating colormaps of scientific simulation data, that can overcome the visualization problems using noise-reduction-based parameter tuning of color control points and a wave-like colormap enhancement in brightness. Several real-world simulation data are used to verify the effectiveness of our proposed method, which means that our method could help domain scientists understand complicated data more clearly and quickly. © Proceedings of the 14th IADIS international conference Computer Graphics, Visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS international conference big data Analytics, data mining and Computational Intelligence 2020, bigDaCI 2020 and Proceedings of the 9th IADIS international conference theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： data visualization

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Researches on data Processing and data Preventing Technologies in the Environment of big data in Power System 5

Researches on Data Processing and Data Preventing Technologi...

引用

5th international conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Li, Nige Xu, Min Cao, Wantian Gao, Peng State Grid Smart Grid Res Inst Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467371063

In this paper, we mainly focus on the problems of the data processing and data security in the environment of the electricity big data systems. Firstly, we focused on the security of big data storage, as well as the big data applications, including the classification, aggregation and data mining demands. We proposed several practicable schemes to the big data applications. After that, we studied on the problem of the privacy prevention in big data processing. In this paper, we analyzed the demands of the big data privacy prevention in smart grid, and also proposed several methods. Based on the previous researches, we put forward the outline of the research hotspots for the data protection.

关键词： Smart Grid big data data processing data mining big data security

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Research on Fashion Design Based on Human-Computer Interaction Technology in the Era of big data 5

Research on Fashion Design Based on Human-Computer Interacti...

引用

5th international conference on Information Science, Computer Technology and Transportation (ISCTT)

作者： Yang, Shuo Liu, Weidong Xu, Congxiao Changsha Univ Sci & Technol Inst Art & Design Changsha Peoples R China Changsha Univ Sci & Technol Dept Literature & Journalism Changsha Peoples R China

ISBN: (纸本)9781728185750

With the rise of big data, big data technology has been widely used in many industries and fields. However, there are not many related technology applications in the field of fashion design. Considering the characteristics of fashion design information in the era of big data, this paper establishes the information database of fashion design, introduces data mining technology to deeply mine the information of various elements of fashion design, and designs the information query system of fashion design by using human-computer interaction tools, which provides reference for the design ideas of fashion designers and realizes the exchange and sharing of big data. the human-computer interaction system can provide objective design basis and scientific design method for fashion design. It is a bold attempt to combine advanced information technology with traditional fashion design field, and is helpful to promote the liberation of thinking in fashion design field.

关键词： fashion design big data information database human-computer interaction information query system

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