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Technical Research on the Electric Power Big Data Platform of Smart Grid

MA Ruiguang, Wang Haiyan, Zhang Quanming, Liang Yuan, Bing Xu, Yinong Chen
2017 MATEC Web of Conferences  
power big data and the excavation technology based on electric power big data, to achieve the breakthrough of key technologies of electric power big data.  ...  Through elaborating on the associated relationship among electric power big data, cloud computing and smart grid, this paper put forward general framework of electric power big data platform based on the  ...  Research on the Mining Technology Based on Electric Power Big Data The mining of electric power big data refers to extracting knowledge from complex data set to assist with decisionmaking mainly through  ... 
doi:10.1051/matecconf/201713900217 fatcat:lh23zz5wfbb6rax3bwu3kx2a5q

Construction of Structured Heterogeneous Networks from Massive Text Data

Jiawei Han
2017 Proceedings of the 2nd International Workshop on Network Data Analytics - NDA'17  
Much real-world data is unstructured, in the form of natural language text.  ...  We present our recent progress on developing effective methods for mining structures from massive text data and constructing structured heterogeneous information networks.  ...  Acknowledgement Research was sponsored in part by the U.S. Army Research Lab. under Cooperative Agreement No. W911NF-09-2-0053 (NSCTA), National Science Foundation IIS-1320617 and IIS  ... 
doi:10.1145/3068943.3068944 dblp:conf/sigmod/Han17 fatcat:y6xtuh6nu5c6pdlblt3e64hvsa

Intricacies of Unstructured Data

Rajeshwari K Rai
2017 EAI Endorsed Transactions on Scalable Information Systems  
Handling the unprecedented growth of unstructured data is a big challenge faced by most data scientists.  ...  This paper discusses about the types and sources of unstructured data and effective ways of processing and analysing this data.  ...  Comprehensive extraction of useful insights from unstructured data is not being done. Most data mining techniques can only handle structured or semi structured data.  ... 
doi:10.4108/eai.25-9-2017.153151 fatcat:psvpfdrjqvdbnecztb4qwynkau


Matthew Sadiku, Justin Foreman, Sarhan Musa
2020 International Journal of Engineering Technologies and Management Research  
The use of digital devices and systems such smart phones, computers, the Internet, and social media has resulted in a massive volume of data which is exponentially increasing daily.  ...  Big data analytics is the process of examining large amounts of data (big data) to uncover hidden patterns, correlations, and other insights.  ...  Also known as text mining or natural language processing, text analytics is the science of turning unstructured text into structured data.  ... 
doi:10.29121/ijetmr.v5.i9.2018.287 fatcat:gi2swpl2rbbd3dt337mxzqpmhy

Survey on Data-intensive Applications, Tools and Techniques for Mining Unstructured Data

Santhosh Voruganti
2016 International Journal of Computer Applications  
And the amount of unstructured data in enterprises is growing significantly. Often many times faster than structured databases .Unstructured data files often include text and multimedia content.  ...  Due to this high explosion it"s really a big challenge to store, manage and access knowledge. Experts estimate that 80 to 90 percent of the data in any organization is unstructured.  ...  INTRODUCTION Historically Natural Language Processing (NLP) focuses on unstructured data (speech and text) understanding while Data Mining (DM) mainly focuses on massive, structured or semistructured datasets  ... 
doi:10.5120/ijca2016910946 fatcat:hvcwqmruo5fb7kwq5lfryf27di

Data Mining Applications in Big Data

Lidong Wang, Guanghui Wang
2015 Computer Engineering and Applications Journal  
Data mining is a process of extracting hidden, unknown, but potentially useful information from massive data. Big Data has great impacts on scientific discoveries and value creation.  ...  Some technology progress of data mining and data mining with big data are also presented.  ...  Big data is a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques.  ... 
doi:10.18495/comengapp.v4i3.155 fatcat:w5gqffk5u5aahld5gzp354d6wu

Heterogeneous Data and Big Data Analytics

Lidong Wang
2017 Automatic Control and Information Sciences  
Heterogeneity is one of major features of big data and heterogeneous data result in problems in data integration and Big Data analytics.  ...  The benefits of the confluences among Big Data analytics, deep learning, high performance computing (HPC), and heterogeneous computing are presented.  ...  Traditional Data Mining and Machine Learning, Deep Learning and Big Data Analytics Outlier detection is one of the tasks of data mining.  ... 
doi:10.12691/acis-3-1-3 fatcat:t3yzrk4r2bfornki34khobe4su

Big data with cloud computing: Discussions and challenges

Amanpreet Kaur Sandhu
2022 Big Data Mining and Analytics  
Meanwhile, cloud computing services provide a powerful environment to store large volumes of data.  ...  With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users.  ...  Unstructured data Unstructured data do not follow the formal structure rules of data models. Images, videos, text messages, and social media posts are examples of unstructured data.  ... 
doi:10.26599/bdma.2021.9020016 fatcat:akgbttvcjrdqncvwy7dvgvpq64

Graph Data: The Next Frontier in Big Data Modeling for Various Domains

Angira Amit Patel, Jyotindra Dharwa
2017 Indian Journal of Science and Technology  
chemical structure, gene data, network structure, social network, e-commerce to text data.  ...  Graph is considered as next frontier in the era of Big data due to its flexibility and self-explaining property.  ...  The second 'V' is symbolization of variety of data that emphasis on heterogeneous data (structure, unstructured and semi structure).  ... 
doi:10.17485/ijst/2017/v10i21/112828 fatcat:7qprb6pdxrc3hpv4sk3olu4kmi

Automatic Entity Recognition and Typing in Massive Text Data

Xiang Ren, Ahmed El-Kishky, Heng Ji, Jiawei Han
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
In this tutorial, we introduce data-driven methods to recognize typed entities of interest in massive, domain-specific text corpora.  ...  To extract value from these large, multi-domain pools of text, it is of great importance to gain an understanding of entities and their relationships.  ...  of unstructured big-data.  ... 
doi:10.1145/2882903.2912567 dblp:conf/sigmod/RenEJH16 fatcat:ycuyy6wdt5ffjjucikqbamvbhq

Big data challenge: a data management perspective

Jinchuan Chen, Yueguo Chen, Xiaoyong Du, Cuiping Li, Jiaheng Lu, Suyun Zhao, Xuan Zhou
2013 Frontiers of Computer Science  
Acknowledgements This work was partially done when the authors worked in SA Center for Big Data Research in Renmin University of China.  ...  This Center is funded by a Chinese National "111" Project "Attracting International Talents in Data Engineering Research".  ...  Finally, the big unstructured data are processed through solutions on the extracted structured data. The extracted data are summaries and sketches of the original unstructured data.  ... 
doi:10.1007/s11704-013-3903-7 fatcat:iialac4ksbgkthayla4sioxtcq

Analysis and Review the Data Using Big Data Hadoop

Ankit Jain, Subbulakshmi T.
2016 International Journal of Database Theory and Application  
With this problem, a replacement platform of "big data" tools has arisen to handle sense creating over massive quantities of information, as within the Apache Hadoop massive knowledge Platform.  ...  Huge knowledge may be structured, unstructured or semi-structured, leading to incapability of standard knowledge management ways.  ...  Data Mining for Big Data Data mining includes extracting and analyzing broad amounts of knowledge or information to find models for large data.  ... 
doi:10.14257/ijdta.2016.9.5.21 fatcat:m4ib5pafcvamlcjwkaopioy4em

Data at Scale [chapter]

Alberto Traverso, Frank J. W. M. Dankers, Leonard Wee, Sander M. J. van Kuijk
2018 Fundamentals of Clinical Data Science  
Therefore, the terms big (clinical) data refers to not only a large volume of data, but on a large volume of complex, unstructured and fragmented data coming from different sources.  ...  -The term big (clinical) data refers to not only a large volume of data, but also more on a large volume of complex, unstructured and fragmented data coming from different sources.  ... 
doi:10.1007/978-3-319-99713-1_2 fatcat:k4tm4wfmyjcrtkuwnweb7z3p7q

A Study on Big Data Integration with Data Warehouse

T.K. Das, Arati Mohapatro
2014 International Journal of Computer Trends and Technology  
In the Age of the Big Data, it is important to remodel the existing warehouse system that will help you and your organization make the most of unstructured data with your existing Data Warehouse.  ...  The challenge is not only to store and manage the vast volume of data, but also to analyze and extract meaningful value from it.  ...  Though now SQL supports keyword search based on full text, but it is limited to text searching only.From unstructured text, the extracted information are obtained as a sequence of tokens But the database  ... 
doi:10.14445/22312803/ijctt-v9p137 fatcat:kjtwtyirwzdmbcbbiue2xo3sym

Big Data and IT Network Data Visualization

Lidong Wang
2018 International journal of mathematical, engineering and management sciences  
The challenges of visualization and Big Data analytics in IT network visualization are also discussed.  ...  Visualization with graphs is popular in the data analysis of Information Technology (IT) networks or computer networks.  ...  Big Data technology helps visualize multi-dimensional data including structured data and unstructured data (Cao, 2014) .  ... 
doi:10.33889/ijmems.2018.3.1-002 fatcat:vghrgd2535gfxejhg3qp5yrjq4
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