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International Journal of Data Mining & Knowledge Management Process (IJDKP)
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Views: 180 ijdkp jou
A Systematic Review on Educational Data Mining | Final year Projects 2016 - 2017
 
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Diagnosis of Lung Cancer Prediction System Using Data Mining Classification Techniques
 
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4th International Conference on Computer Science, Information Technology (CSITEC 2018)
 
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June 23 ~24, 2018, Copenhagen, Denmark http://necom2016.org/csitec/index.html Call for Papers 4th International Conference on Computer Science, Information Technology (CSITEC 2018) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science, Engineering and Information Technology in theoretical and practical aspects. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, Topics of Interest Algorithms and Bioinformatics Computer Architecture and Real-Time Systems Database and Data Mining Dependable, Reliable and Autonomic Computing Distributed and Parallel Systems & Algorithms DSP/Image Processing/Pattern Recognition/Multimedia Embedded System and Software Game and Software Engineering Geographical Information Systems/ Global Navigation Satellite Systems (GIS/GNSS) Grid and Scalable Computing Intelligent Information & Database Systems IT policy and Business Management Mobile and Ubiquitous Computing Modeling and Simulation Multimedia Systems and Services Networking and Communications Parallel and Distributed Systems Performance Evaluation Programming Languages Security and Information Assurance Soft Computing (AI, Neural Networks, Fuzzy Systems, etc.) Software Engineering Web and Internet Computing Theoretical Computer Science Natural Language Processing Operating Systems Compiler Design Computer Education Information Technology Management Recent Trends in Information technology e-Learning, e-Business, Enterprise Information Systems and e-Government Paper Submission Authors are invited to submit papers through the Conference Submission System by May 26, 2018. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS&IT) series (Confirmed). Selected papers from CSITEC 2018, after further revisions, will be published in the special issue of the following journal. International Journal of Computer Science & Information Technology (IJCSIT) – UGC, INSPEC Indexed International Journal of Computer science and engineering Survey (IJCSES) Computer Science & Engineering: An International Journal (CSEIJ) Advanced Computing: An International Journal ( ACIJ ) International Journal of Information Technology Convergence and Services (IJITCS) International Journal of Computer Science, Engineering, and Applications (IJCSEA) Important Dates Submission Deadline : May 26, 2018 Authors Notification : June 10, 2018 Registration & Camera-Ready Paper Due : June 15, 2018
Views: 85 IJCSEA Journal
A survey Big Data social media using data mining techniques | | Final Year Projects 2016 - 2017
 
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A Systematic Review on Educational Data Mining
 
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Views: 66 Clickmyproject
Call for Papers for International Journal of Research (IJR)
 
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Authors are invited to submit unpublished papers which are not review in any other journal or conference. International journal of Research (IJR) is directed to researchers, engineers, educators, managers, programmers and users of computers who are interested in computer science engineering. Research area includes but not limited to Image Processing Data Mining Algorithm and Complexity Computer Networks Embedded Systems and Applications Software Engineering Internet Technologies Parallel and Distributed Systems Bioinformatics Social Computing Cooperative Information Systems Pattern Recognition Bayesian Statistics Network and Software Security Control Theory Cloud Computing Optimization Techniques Neural Networks Computer Architecture Stochastic Differential Equations Object Oriented Modeling Software Testing Computer Graphics and Visualization Natural Language Processing Database Management Digital Forensics Peer to Peer and Overlay Networks Computational Mathematics Information Processing Real Time Systems Web Services
Views: 24 EduINDEX Lectures
Diagnosis of Lung Cancer Prediction System  Using Data Mining Classification Techniques
 
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IEEE Transactions on Computers call for papers special section on Computer Arithmetic
 
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IEEE Transactions on Computers seeks original manuscripts for a Special Section on Computer Arithmetic scheduled to appear in the August issue of 2014. Computer arithmetic is fundamental to the design of general-purpose and domain-specific processors. Novel arithmetic algorithms and hardware designs are needed to satisfy the power-performance requirements of numerically-intensive applications in a variety of areas including scientific computing, cryptography, multimedia, graphics and digital signal processing. Specialized number representations and encodings play a significant role in the design of arithmetic algorithms and their implementations. Additionally, understanding the fundamental properties of finite precision number systems is essential in the engineering of efficient arithmetic algorithms, as well as the current and future emerging technologies are important in influencing the design and the implementation of such algorithms. http://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tcsi_arith.pdf
Views: 578 ieeeComputerSociety
To improve Blood Donation Process using Data Mining Techniques | Final Year Projects 2016
 
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Views: 912 Clickmyproject
A Systematic Review on Educational Data Mining
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577 Shop Now @ https://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
Views: 43 myproject bazaar
Would You Rather? SLC takes Data Mining Quiz!
 
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Yes these quizzes are Data-mining methods and I do NOT recommend you partake. I do so to expose what most people are regularly partaking in. Thanks! New World Agenda Links: Youtube Channels: New World Agenda (main channel): https://www.youtube.com/channel/UC3xHAfZZqbMMWjc1ed1ajow Supreme Lord Commander: https://www.youtube.com/channel/ Free Radio Revolution CLASSICS https://www.youtube.com/channel/UCl-03iQuVIb66oZDMCvFAzA Free Radio Revolution Uncensored: https://www.youtube.com/channel/UCIloSv-wrTOPppr6U9JL6aA UCABsCi4KoMTp9VcwEG7_pyA Vidme: Vidme: https://vid.me/FreeRadioRevolu Facebook: Free Radio Revolution: https://www.facebook.com/Free-Radio-Revolution-118389281849019/timeline/ Twitter: @freeradiorevolu https://twitter.com/FreeRadioRevolu
A Workflow Management System for Scalable Data Mining on Clouds
 
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Views: 105 Clickmyproject
A Review on Mining Students’ Data for Performance Prediction  | Final Year Projects 2016 - 2017
 
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Stream Data Mining: A Big Data Perspective
 
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Author: Latifur Khan, Department of Computer Science, Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas Abstract: Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Data streams demonstrate several unique properties that together conform to the characteristics of big data (i.e., volume, velocity, variety and veracity) and add challenges to data stream mining. In this talk we will present an organized picture on how to handle various data mining techniques in data streams. Most existing data stream classification techniques ignore one important aspect of stream data: arrival of a novel class. We address this issue and propose a data stream classification technique that integrates a novel class detection mechanism into traditional classifiers, enabling automatic detection of novel classes before the true labels of the novel class instances arrive. Novel class detection problem becomes more challenging in the presence of concept-drift, when the underlying data distributions evolve in streams. In this talk we will show how to make fast and correct classification decisions under this constraint with limited labeled training data and apply them to real benchmark data. In addition, we will present a number of stream classification applications such as adaptive malicious code detection, website fingerprinting, evolving insider threat detection and textual stream classification. This research was funded in part by NSF, NASA, Air Force Office of Scientific Research (AFOSR) and Raytheon. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 940 KDD2016 video
Algorithmic Bias: From Discrimination Discovery to Fairness-Aware Data Mining (Part 1)
 
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Authors: Carlos Castillo, EURECAT, Technology Centre of Catalonia Francesco Bonchi, ISI Foundation Abstract: Algorithms and decision making based on Big Data have become pervasive in all aspects of our daily lives lives (offline and online), as they have become essential tools in personal finance, health care, hiring, housing, education, and policies. It is therefore of societal and ethical importance to ask whether these algorithms can be discriminative on grounds such as gender, ethnicity, or health status. It turns out that the answer is positive: for instance, recent studies in the context of online advertising show that ads for high-income jobs are presented to men much more often than to women [Datta et al., 2015]; and ads for arrest records are significantly more likely to show up on searches for distinctively black names [Sweeney, 2013]. This algorithmic bias exists even when there is no discrimination intention in the developer of the algorithm. Sometimes it may be inherent to the data sources used (software making decisions based on data can reflect, or even amplify, the results of historical discrimination), but even when the sensitive attributes have been suppressed from the input, a well trained machine learning algorithm may still discriminate on the basis of such sensitive attributes because of correlations existing in the data. These considerations call for the development of data mining systems which are discrimination-conscious by-design. This is a novel and challenging research area for the data mining community. The aim of this tutorial is to survey algorithmic bias, presenting its most common variants, with an emphasis on the algorithmic techniques and key ideas developed to derive efficient solutions. The tutorial covers two main complementary approaches: algorithms for discrimination discovery and discrimination prevention by means of fairness-aware data mining. We conclude by summarizing promising paths for future research. More on http://www.kdd.org/kdd2016/ KDD2016 conference is published on http://videolectures.net/
Views: 1738 KDD2016 video
A Data Mining Approach Combining K-Means Clustering with Bagging Neural Network
 
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Views: 68 Clickmyproject
A Review Paper on Dengue Disease Forcasting Using Data Mining Techniques
 
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Views: 60 Clickmyproject
Final Year Projects 2015 | Soil Classification Using  Data Mining  Techniques
 
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Views: 637 myproject bazaar
A Review Paper on Dengue Disease Forcasting Using Data Mining Techniques
 
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Views: 56 myproject bazaar
KDD2016 paper 575
 
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Title: Dynamic and Robust Wildfire Risk Prediction System: An Unsupervised Approach Authors: Mahsa Salehi*, IBM Australia Laura Rusu, IBM Research Timothy Lynar, IBM Research Anna Phan, IBM Research Abstract: Ability to predict the risk of damaging weather events (e.g. wildfires) is crucial in helping emergency services in their decision-making processes, to mitigate and reduce the severity of such events. Today, wildfire rating systems have been in operation extensively in many countries around the world to estimate the danger of wildfires. In this paper we propose a data-driven approach to predict the wildfire risk. We show how we address the inherent challenges of such an approach that arise mainly due to the temporal dynamicity of weather data. Weather observations naturally change in time, with finer-scale variation (e.g. stationary day or stationary night) or large variations (non-stationary day or night), and this determines a temporal variation of the predicted fire danger. We show how our dynamic wildfire danger prediction model addresses the aforementioned challenges using context-based anomaly detection techniques and can be customized to different regions. We call our predictive model a Context-Based Fire Risk (CBFR) model. The advantage of our model is that it maintains multiple historical models for different temporal variations (e.g. day versus night), and use ensemble learning techniques to predict wildfire risk with high accuracy. In addition, it is completely unsupervised and does not rely on expert knowledge, which makes it flexible and easy to be applied in any region of interest. Our CBFR model is also scalable and can potentially be parallelized to speed up computation. Considering multiple wildfires (a.k.a. bushfires in Australia) locations in the Blue Mountains 2013 bushfires, Australia as a case study, we have compared the results of our system with the existing well-established Australian bushfire rating system. The experimental results show that our predictive model has a substantially higher accuracy in predicting the fire risk, which makes it an effective model to supplement the operational Australian bushfire rating system. More on http://www.kdd.org/kdd2016/ KDD2016 Conference will be recorded and published on http://videolectures.net/
Views: 4298 KDD2016 video
Soil Classification Using  Data Mining  Techniques | Final Year Projects 2016
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://myprojectbazaar.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/myprojectbazaar Mail Us: [email protected]
Views: 152 myproject bazaar
An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 881 Clickmyproject
Final Year Projects | Enabling Multilevel Trust in Privacy Preserving Data Mining
 
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Final Year Projects | Enabling Multilevel Trust in Privacy Preserving Data Mining More Details: Visit http://clickmyproject.com/a-secure-erasure-codebased-cloud-storage-system-with-secure-data-forwarding-p-128.html Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 1452 Clickmyproject
Final Year Projects 2015 | Automated web usage data mining and recommendation system
 
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Views: 3390 Clickmyproject
Improved churn prediction in telecommunication industry using datamining techniques
 
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Views: 129 Clickmyproject
A Survey on Trajectory Data Mining: Techniques and Applications | Final Year Projects 2016 - 2017
 
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A Novel Data Mining Approach for Soil Classification | Final Year Projects 2016 - 2017
 
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Views: 65 Clickmyproject
NTICT 2018 Conference
 
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The 3rd International Conference on New Trends in Information & Communications Technology (NTICT 2018) is a specialized conference that aims to present the latest researches related to new trends in Information & Communications Technology Applications. NTICT 2018 aims to identify prospects and solutions for development of this important sectors as well as to contribute for building an informatics society in the world. The conference is organized by University of Information Technology and Communications (UoITC), and will be held on October 2nd - 4th, 2018 in Baghdad-Iraq. The conference will be regularly held to make it an ideal platform for participants to share views and experience in Information & Communications Technology. It is planned to publish the proceedings with Springer in their Communications in Computer and Information Science series (CCIS) (final approval pending). CCIS is abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus. CCIS volumes are also submitted for the inclusion in ISI Proceedings. Prospective authors are invited to submit full paper with (12-15) pages in single-column following Springer conference paper templates, which can be find in the author’s instruction page in https://goo.gl/r83B1W. More information about paper format and guidelines for paper submission can be found at the conference website. NTICT 2018 will feature both contributed and invited papers. For more information, please send your inquiry to: [email protected] You may also call us at +964-7822786793. [Conference Webpage] http://www.uoitc.edu.iq/conf/index.html [Important dates] Paper submission: 15 April 2018 Notification of acceptance: 15 June 2018 Final manuscript submission: 15 July 2018 Conference dates: October 02-04, 2018 [Venue] Educational Complex-MOHE-Ahmed BinFadhlan Hall, Ministry of Higher Education. [Technical areas] 1. Computer Networks and Communications • Adhoc and sensor networks • High speed networks • Internet and Web applications • Mobile networks • Network Architectures • Network Operations & management • Network Protocols and Wireless Networks • Network Security • Next Generation Internet • Peer to peer and overlay networks • QoS and Resource Management • Routing, switching and addressing techniques • Self-Organizing Networks • Wireless Multimedia systems • Social Network Applications 2. Artificial Intelligence and Machine Learning • Adaptive Control • Ambient Intelligence • Bayesian Networks • Autonomous Agents • Bio-informatics • Cognitive Modeling • Computer Animation • Computer Vision • Data Mining • Decision Support Systems • Game Theory • Evolutionary Algorithms • Expert Systems • Heuristic Search • Intelligent Systems • Knowledge Processing • Machine Learning • Multi-Agent Systems • Natural Language Processing • Planning and Scheduling • Speech Recognition • Web Semantics and Ontologies We all look forward to seeing you at Baghdad-Iraq in October 2018. Sincerely, Your 3rd NTICT 2018 Conference Organizing Committee
Predicting the Winning Team with Machine Learning
 
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Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool. Code for this video: https://github.com/llSourcell/Predicting_Winning_Teams Please Subscribe! And like. And comment. More learning resources: https://arxiv.org/pdf/1511.05837.pdf https://doctorspin.me/digital-strategy/machine-learning/ https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/ http://data-informed.com/predict-winners-big-games-machine-learning/ https://github.com/ihaque/fantasy https://www.credera.com/blog/business-intelligence/using-machine-learning-predict-nfl-games/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 98648 Siraj Raval
How "Big Data" Can Predict Your Divorce
 
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http://news.yahoo.com/blogs/this-could-be-big-abc-news/finding-meaning-human-data-mining-041552391.html http://www.youtube.com/user/ABCNews For Information / Fair Use only. No copyright infringement intended. If you are the owner and feel that it should be remove please notify asap. How "Big Data" Can Predict Your Divorce By Bill Weir, C. Michael Kim, David Miller, Justin Bare & Mark Monroy | This Could Be Big As our lives become more enmeshed in the digital playground, we reveal more information about ourselves than ever before in the history of mankind. Every online search, store purchase, Facebook post, Tweet or Foursquare check-in is creating a flood of data that, when organized and categorized and analyzed, reveals trends and habits about ourselves and society at large. In the last two years, humans have created 90% of all information ever created by our species. If our data output used to be a sprinkler, it is now a firehose that's only getting stronger, and it is revealing information about our relationships, health, and undiscovered trends in society that are just beginning to be understood. In his new book The Human Face of Big Data, author and photographer Rick Smolan and his partner Jennifer Erwitt use pictures, essays and startling facts to put our unprecedented output of information into perspective. Mr. Smolan sat down with us this week to discuss some of what he discovered and his findings are mind-blowing and illuminate the scope of information being put forth by people on a daily basis. To correspond with the release of the book, which went on sale December 4th, 2012, 10,000 copies were sent to some of world's most influential people including, United Nations Secretary General Ban Ki-moon, UK Prime Minister David Cameron, Oprah Winfrey and Warren Buffett.
Views: 6858 C. Allen Johnson
Earthquake Prediction based on Spatio-Temporal Data Mining: An LSTM Network Approach
 
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Views: 43 Elysium pro
International Journal of Information Technology, Modeling and Computing (IJITMC)
 
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International Journal of Information Technology, Modeling and Computing (IJITMC) http://airccse.org/journal/ijitmc/index.html ISSN : 2320-7493 (Online) ; 2320 - 8449 (Print) Call for papers The International Journal of Information Technology, Modeling and Computing (IJITMC) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology, Modeling and Computing. With the advances of Information Technology, there is an active multi-disciplinary research in the areas of IT, CSE, Modeling and Simulation with numerous applications in various fields. The International Journal of Information Technology, Modeling and Computing (IJITMC) is an abstracted and indexed international journal of high quality devoted to the publication of original research papers from IT, Modeling, CSE and Control Engineering with some emphasis on all areas and subareas of computer science, IT, scientific modeling, simulation, visualization and control systems and their broad range of applications. Areas and subareas of interest include (but are not limited to): • Advanced computing techniques • Algorithm and analysis • Automation • Bio-informatics • Bio-modeling and applications • Chaos theory and control • Compression techniques • Computer graphics • Computer vision • Control applications • Control theory • Cryptography and applications • Data encryption • Data Mining • Digital image processing • Digital signal processing • Evolutionary algorithms • Filtering • Flight control and surveillance systems • Fuzzy logic and control • Genetic algorithms and applications • Guidance control systems • Image processing • Industrial applications • Information networking • Intelligent and natural computing • Intelligent systems • Mathematical control theory • Modeling and visualization • Multimedia computing • Multimedia systems • Networks and Computing • Neural networks • Nonlinear control systems • Navigation • Pattern recognition • Process control and instrumentation • Robotics and applications • Robust control • Secure communication • Secure systems • Scientific and engineering modeling • Signal processing • Soft computing techniques in control • Stochastic control and filtering theory • System Science and Engineering • System identification and modeling • Systems and automation • System modeling and control Paper Submission Authors are invited to submit papers for this journal through E-mail : [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijitmc/index.html
Views: 14 aircc Journal
Application of data mining: Diabetes health care in young | Final Year Projects 2016 - 2017
 
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Views: 253 myproject bazaar
PPDM and Data Mining Technique Ensures Privacy and Security | Final Year Projects 2016 - 2017
 
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Data Mining and Analytics in the Process Industry: The Role of Machine Learning
 
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Views: 33 Clickmyproject
Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction
 
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Views: 93 myproject bazaar
A Workflow Management System for Scalable Data Mining on Clouds
 
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Views: 43 myproject bazaar
Mining Human Activity Patterns From Smart Home Big Data for Health Care Applications
 
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Views: 102 Clickmyproject
Data mining in lung cancer pathologic staging diagnosis: Correlation-clinical&pathology information
 
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Views: 131 Clickmyproject
Applications of Predictive Analytics in Legal | Litigation Analytics, Data Mining & AI | Great Lakes
 
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#PredictiveAnalytics | Learn the prediction of outcome or treatment of a case by legal courts of Appeals based on historical data using predictive analytics. Watch the video to understand analytics in legal using case study on real-life data set. How litigation analytics can flourish with the use of data mining and AI. Know more about our analytics Program: PGP- Business Analytics: https://goo.gl/V9RzVD PGP- Big Data Analytics: https://goo.gl/rRyjj4 Business Analytics Certification Program: https://goo.gl/7HPoUY #LegalTech #LegalAnalytics #GreatLearning #GreatLakes About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube
Views: 1039 Great Learning
Wind Turbine Accidents: A Data Mining Study |Final year projects 2018 - 2019
 
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Views: 15 myproject bazaar
Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction
 
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Views: 77 Clickmyproject
Final Year Projects | An Ontology-Based Text-Mining Method to Cluster Proposals for Research
 
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Final Year Projects | An Ontology-Based Text-Mining Method to Cluster Proposals for Research Project Selection More Details: Visit http://clickmyproject.com/a-secure-erasure-codebased-cloud-storage-system-with-secure-data-forwarding-p-128.html Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 3518 Clickmyproject
Final Year Projects 2015 | Automated web usage data mining and recommendation system
 
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Views: 553 Clickmyproject
Wind Turbine Accidents: A Data Mining Study
 
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Views: 11 Clickmyproject
Health Informatics - An International Journal (HIIJ)
 
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Health Informatics - An International Journal (HIIJ) ISSN : 2319 - 2046 (Online); 2319 - 3190 (Print). http://airccse.org/journal/hiij/index.html Call for papers Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care. The journal focuses on all of aspect in theory, practices, and applications of Digital Health Records, Knowledge Engineering in Health, E-Health Information,and Information Management in healthcare, Bio-Medical Expert Systems, ICT in health promotion and related topics. Original contributions are solicited on topics covered under the broad areas such as (but not limited to) listed below: Topics of interest include, but are not limited to, the following: • Electronic health records • Knowledge engineering • E-Health Information • Information Management in healthcare • Expert Systems in Biomdical • Communication System in Helthcare • Artificial Intelligence in Medicine and Health Sciences • Ontological Engineering in Medicine • Health Care Information Systems. • Knowledge management in Healthcare • Clinical Information Systems. • Bioinformatics and Biostatistics. • Mobile applications for patient care • Medical Interoperability • Medical Devices and sensors • Impact and usability • Medical Image Processing and Techniques. • ICT in health promotion programmes • e-health Guidelines and protocols • E-learning and education in healtcare • Telemedicine Software, Portals, Devices and Telehealth. • Public health and consumer informatics • Data Mining and Knowledge Discovery in Medicine. • ICT for Patient empowerment • ICT for Patient safety • Medical Databanks, Databases, and Knowledge Bases. • Neurocomputing in Medicine. • Healthcare Quality assurance • Nursing Informatics • Evaluation and technology assessment • Home-based eHealth • Health Management Issues • Health Research • Health Economics Issues Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/hiij/index.html
Views: 25 hiij journal4
Disease Prediction by Machine Learning over Big Data from Healthcare Communities
 
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Views: 1234 myproject bazaar
Recommender Problems for Web Applications, 4/26/2010
 
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Please also see http://www.sfbayacm.org/?p=1579 for links to the presentation slides and other related documents. DESCRIPTION: Several web applications like content optimization and online advertising involve recommending items from an inventory for each user visit to maximize some yield metric of interest (e.g. click rates). These are instances of large scale recommender system problems that entail several statistical challenges. We provide a mathematical description of the problem followed by modeling solutions for a content optimization problem that arises in the context of Yahoo! Front Page (www.yahoo.com). In fact, we discuss models to a) serve most popular items, b) serve items that are most popular in different user segments and c) provide personalized item recommendations for each user. Our models are based on time series methods, multi-armed bandit schemes and bilinear random effects model. One class of bilinear random effects model we propose extends reduced rank regression to incomplete matrices, the other class extends matrix factorization to incorporate covariates. Throughout, concepts are illustrated with examples and results obtained from "bucket tests" conducted on a real system. SPEAKER BIOGRAPHY: Deepak Agarwal is currently a Principal research scientist at Yahoo! Research. Prior to joining Yahoo!, he was a member of the statistics department at AT&T Research. He is a statistician interested in scalable modeling approaches for large scale applications. He has done extensive research on large scale hierarchical random effects model, computational advertising, modeling massive social networks with applications to call graph that arise in the telecommunications industry and modeling massive dyadic data that arise in applications like recommender systems. He has won four best paper awards (JSM 2001, SDM 2004, KDD 2007, ICDM 2009) that are directly related to the material of the talk. He has also done research in anomaly detection using a time series approach and computational approaches for scaling spatial scan statistic to large data sets. He regularly serves on program committees of data mining and machine learning conferences. He is currently associate editor for Journal of Americal Statistical Association, the top journal in the field of Statistics. He have given two tutorials on Statistical Challenges in Online Advertising at CIKM 2009 and KDD 2009. Deepak in collaboration with his co-authors have developed algorithms for real recommender systems that have been successfully deployed and thus has experience with both practical and scientific issues that arise in such applications. More info available at http://www.sfbayacm.org/?p=1579
Views: 2396 San Francisco Bay ACM

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