Conferences related to Data Analytics

Back to Top

2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2019 IEEE International Ultrasonics Symposium (IUS)

The conference covers all aspects of the technology associated with ultrasound generation and detection and their applications.


2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA)

Industrial Informatics, Computational Intelligence, Control and Systems, Cyber-physicalSystems, Energy and Environment, Mechatronics, Power Electronics, Signal and InformationProcessing, Network and Communication Technologies


2018 19th IEEE International Conference on Mobile Data Management (MDM)

The conference aims to attract original research contributions in the interesection of mobile computing and data management. Topics of interest include, but not limited to:- Mobile Cloud Computing and Data Management - Data Management for Internet of Things (IoT) and Sensor Systems- Data Management for Augmented Reality Systems- Data Management for Intelligent Transportation Systems, Smart Spaces- Mobile Crowd-Sourcing and Crowd-Sensing- Mobile Data Analytics- Behavioural/Activity Sensing and Analytics- Mobile Location-Based Social Networks- Mobile Recommendation Systems- Context-aware Computing for Intelligent Mobile Services- Middleware and Tools for Mobile and Pervasive Computing- Theoretical Foundations of Data-intensive Mobile Computing- Data Stream Processing in Mobile/Sensor Networks- Indexing, Optimisation and Query Processing for Moving Objects/Users- Security and Privacy in Mobile Systems

  • 2017 18th IEEE International Conference on Mobile Data Management (MDM)

    Mobile computing and data management

  • 2016 17th IEEE International Conference on Mobile Data Management (MDM)

    The Mobile Data Management series of conferences first debuted in December 1999. Since inception, it has established itself as a prestigious forum to exchange innovative and significant research results in mobile data management. Comprising both research and industry tracks, it serves as an important bridge between academic researchers and industry researchers. Along with the presentations of research publications, it also serves as a meeting place for technical demonstrations (Demos), workshops, panel discussions as well as PhD forum and Industrial forum to cater PhD students and industrial developers.The conference focuses on research contributions in data management in mobile, ubiquitous and pervasive computing.

  • 2015 16th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2014 15th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility

  • 2013 14th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2012 13th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2011 12th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas.

  • 2010 11th International Conference on Mobile Data Management (MDM)

    The annual MDM conference is a leading international forum that focuses on data management for mobile, ubiquitous, and pervasive computing. It brings together a wide range of researchers, practitioners, and users to explore scientific and industrial challenges that arise in the areas of data management and mobile computing.

  • 2008 9th International Conference on Mobile Data Management (MDM)

  • 2007 International Conference on Mobile Data Management (MDM)

  • 2006 International Conference on Mobile Data Management (MDM)

  • 2004 IEEE International Conference on Mobile Data Management (MDM)


2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)

We invite submissions of high quality papers describing fully developed results or on-going foundational and applied work on the following topics:Agent for e-Business TrackData and Big Data for e-Business TrackInternet of Things (IoT) and Edging/Fog Computing TrackMobile and Autonomous Computing TrackSecurity, Privacy, Trust, and Credit TrackService-Oriented and Cloud TrackSoftware Engineering for e-Business TrackEmerging Ecommerce Supporting Technologies (Blockchain / Nature Language Engineering / Smart Brokers) Track

  • 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)

    New IT breakthrough always brings the evolution of e-business in wide spectrum, e.g. innovative business model, new marketing and sales channel, rapid sense-and-response, etc. How to adapt the changing computing paradigm and adopt new IT technologies for keeping competitive is a great challenge for modern enterprises. Based on the essential complexities in e-business, ICEBE 2017 invites an extensive coverage of system, software, service, business and combinations of the aforementioned etc.

  • 2016 IEEE International Conference on e-Business Engineering/Service-Oriented Computing and Applications (ICEBE/SOCA)

    E-Business, Service-Oriented Architecture, Cloud-based E-Business, Data Analytics for IoT Applications

  • 2015 IEEE 12th International Conference on e-Business Engineering (ICEBE)

    New IT breakthrough always brings the evolution of e-business in wide spectrum, e.g. innovative business model, new marketing and sales channel, rapid sense-and-response, etc. How to adapt the changing computing paradigm and adopt new IT technologies for keeping competitive is a great challenge for modern enterprises. Based on the essential complexities in e-business, ICEBE 2015 invites an extensive coverage of system, software, service, business and combinations of the aforementioned etc.

  • 2014 IEEE 11th International Conference on e-Business Engineering (ICEBE)

    ICEBE 2014 is a prestigious conference since 2003. As a flagship event sponsored by IEEE Technical Committee on Business Informatics and Systems (TCBIS, formerly known as TC on Electronic Commerce), ICEBE is a high-quality international forum for researchers, engineers and business specialists to exchange the cutting-edge ideas, findings and experiences of e-business.New IT breakthrough always brings the evolution of e-business in wide spectrum, e.g. innovative business model, new marketing and sales channel, rapid sense-and-response, etc. How to adapt the changing computing paradigm and adopt new IT technologies for keeping competitive is a great challenge for modern enterprises. Based on the essential complexities in e-business, ICEBE 2014 invites an extensive coverage of system, software, service, business and combinations of the aforementioned etc.

  • 2013 IEEE 10th International Conference on e-Business Engineering (ICEBE)

    e-Commerce Platforms, Models and Applications, Workflows and Transactions in e-Business, Management and Engineering of IT Enabled Services, Requirement Analysis and Modeling, Dependability and Performance, Business Performance Management, Data and Knowledge Engineering, Mobile and Pervasive Commerce Security, Privacy in e-Commerce, Open Source Technologies in E-Commerce/Business/Services, Cloud Computing, Industry Experience and Applications, IoT

  • 2012 IEEE 9th International Conference on e-Business Engineering (ICEBE)

    E-Commerce Platforms, Models and Applications, Workflows and Transactions in E-Business, Management and Engineering of IT Enabled Services, Requirement Analysis and Modeling, Dependability and Performance, Business Performance Management, Data and Knowledge Engineering, Mobile and Pervasive Commerce Security, Privacy in E-Commerce, Open Source Technologies in E-Commerce/Business/Services, Cloud Computing, Industry Experience and Applications, IoT

  • 2011 IEEE 8th International Conference on e-Business Engineering (ICEBE)

    IoT, E-Commerce Platforms, Models and Applications, Workflows and Transactions in E-Business, Management and Engineering of IT Enabled Services, Requirement Analysis and Modeling, Dependability and Performance, Business Performance Management, Data and Knowledge Engineering, Mobile and Pervasive Commerce Security, Privacy in E-Commerce, Open Source Technologies in E-Commerce/Business/Services, Cloud Computing, Industry Experience and Applications.

  • 2010 IEEE 7th International Conference on e-Business Engineering (ICEBE)

    E-Commerce Platforms, Models and Applications, Workflows and Transactions in E-Business, Management and Engineering of IT Enabled Services, Requirement Analysis and Modeling, Dependability and Performance, Business Performance Management, Data and Knowledge Engineering, Mobile and Pervasive Commerce Security, Privacy in E-Commerce, Open Source Technologies in E-Commerce/Business/Services, Cloud Computing, Industry Experience and Applications

  • 2009 IEEE International Conference on e-Business Engineering (ICEBE)

    The main themes of this year s conference will be enabling integrated e -business systems through servicing and collaboration , which is distributed in the following program tracks: - Software engineering for e -business - Data and knowledge management - Service engineering - Integration and collaboration - Security, privacy and open sources - Mobile and pervasive commerce - Industrial experiences and applications

  • 2008 IEEE International Conference on e-Business Engineering (ICEBE)

    E-Commerce Platforms, Models and Applications, Workflows and Transactions in E-Business, Management and Engineering of IT-Enabled Services, Requirement Analysis and Modeling of E-Business Systems, Dependability and Performance of E-Business Systems, Business Performance Management, Data and Knowledge Engineering for E-Business, Mobile and Pervasive Commerce Security, Privacy in E-Commerce, Open Source Technologies in E-Commerce/Business/Services

  • 2007 IEEE International Conference on e-Business Engineering (ICEBE)

    E-Commerce Platforms, Models and Applications, Workflows and Transactions in E-Business, Management and Engineering of IT-Enabled Services, Requirement Analysis and Modeling of E-Business Systems, Dependability and Performance of E-Business Systems, Business Performance Management, Data and Knowledge Engineering for E-Business, Mobile and Pervasive Commerce Security, Privacy in E-Commerce, Open Source Technologies in E-Commerce/Business/Services

  • 2006 IEEE Conference on e-Business Engineering (ICEBE)

  • 2005 IEEE Conference on e-Business Engineering (ICEBE)


More Conferences

Periodicals related to Data Analytics

Back to Top

Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computer Graphics and Applications, IEEE

IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...


Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on

Methods, algorithms, and human-machine interfaces for physical and logical design, including: planning, synthesis, partitioning, modeling, simulation, layout, verification, testing, and documentation of integrated-circuit and systems designs of all complexities. Practical applications of aids resulting in producible analog, digital, optical, or microwave integrated circuits are emphasized.


More Periodicals


Xplore Articles related to Data Analytics

Back to Top

CityPulse: Large Scale Data Analytics Framework for Smart Cities

IEEE Access, 2016

Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains, ...


Data analytics 2014

Data Analytics 2014: The Rising Role of Big Data, 2014

The following topics are dealt with: data analytics; big healthcare data; smarter city analysis; transport data; and smart meter data.


Big social data analytics of changes in consumer behaviour and opinion of a TV broadcaster

2016 IEEE International Conference on Big Data (Big Data), 2016

This paper examines the changes in consumer behaviour and opinions due to the transition from a public to a commercial broadcaster in the context of broadcasting international media events. By analyzing TV viewer ratings, Facebook activity and its sentiment, we aim to provide answers to how the transition from airing Winter Olympic Games on NRK to TV2 in Norway affected ...


Platforms for big data analytics: Trend towards hybrid era

2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), 2017

The primary objective of this paper is to present detailed analysis of various platforms suitable for Big Data processing. In this paper, various software frameworks available for Big Data analytics are surveyed and in-detail assessment of their strengths and weaknesses is discussed. In addition to this, widely used data mining algorithm are discussed for their adaptation for Big Data analysis ...


Execution Models for Mobile Data Analytics

IT Professional, 2017

Execution models enable mobile data analytics applications to run on multiple platforms, but these applications need to handle massive heterogeneity. This article discusses various options for designing execution models and presents related challenges.


More Xplore Articles

Educational Resources on Data Analytics

Back to Top

IEEE.tv Videos

Big Data Analytics: Tools and Technologies - Big Data Analytics Tutorial Part 2
Mahmoud Daneshmand on IoT and Big Data Analytics: IoT: Even Bigger Data
Big Data and Analytics at Verizon
Jeff Voas on the Internet of Things and Big Data Analytics - WF-IoT 2015
Kazunori Iwasa: Challenges in Controlling Data Center Facilities - IoT Challenges Industry Forum Panel: WF IoT 2016
Q&A with Chris Franzino: IEEE Big Data Podcast, Episode 5
Challenges and SP Tools for Big Data Analytics
May Wong on Making Sense of BIG Biomedical DATA - WF-IoT 2015
The Role of Data Analytics in AI - Nick Saunders - VIC Summit 2019
Merge Network for a Non-Von Neumann Accumulate Accelerator in a 3D Chip - Anirudh Jain - ICRC 2018
Netflix's Chris Pouliot: How to Build a Data Science Team from Scratch
Edge To Core To Cloud IoT infrastructure For Distributed Analytics - Yogev Shimony and Phil Hummel, Fog World Congress 2017
"What is Big Data Analytics and Why Should I Care?" - Big Data Analytics Tutorial Part 1
Q&A with Dr. May Wang: IEEE Big Data Podcast, Episode 9
NGD Systems Pitch: Fog Tank - Fog World Congress
Rebooting Computing Research at the Laboratory for Physical Sciences - Gil Herrera: 2016 International Conference on Rebooting Computing
Tech Super Stars Panelist - Vincent Chan: 2016 Technology Time Machine
Time-series Workloads and Implications for Time-series Databases - Michael Freedman - IEEE Sarnoff Symposium, 2019
Q&A with Kathy Grise: IEEE Big Data Podcast, Episode 6
Forecube Pitch: Fog Tank - Fog World Congress

IEEE-USA E-Books

  • CityPulse: Large Scale Data Analytics Framework for Smart Cities

    Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains, such as healthcare, environmental monitoring, urban systems, and control and management applications, among several other areas. Cities currently face an increasing demand for providing services that can have an impact on people's everyday lives. The CityPulse framework supports smart city service creation by means of a distributed system for semantic discovery, data analytics, and interpretation of large-scale (near-)real-time Internet of Things data and social media data streams. To goal is to break away from silo applications and enable cross-domain data integration. The CityPulse framework integrates multimodal, mixed quality, uncertain and incomplete data to create reliable, dependable information and continuously adapts data processing techniques to meet the quality of information requirements from end users. Different than existing solutions that mainly offer unified views of the data, the CityPulse framework is also equipped with powerful data analytics modules that perform intelligent data aggregation, event detection, quality assessment, contextual filtering, and decision support. This paper presents the framework, describes its components, and demonstrates how they interact to support easy development of custom-made applications for citizens. The benefits and the effectiveness of the framework are demonstrated in a use-case scenario implementation presented in this paper.

  • Data analytics 2014

    The following topics are dealt with: data analytics; big healthcare data; smarter city analysis; transport data; and smart meter data.

  • Big social data analytics of changes in consumer behaviour and opinion of a TV broadcaster

    This paper examines the changes in consumer behaviour and opinions due to the transition from a public to a commercial broadcaster in the context of broadcasting international media events. By analyzing TV viewer ratings, Facebook activity and its sentiment, we aim to provide answers to how the transition from airing Winter Olympic Games on NRK to TV2 in Norway affected consumer behaviour and opinion. We used text classification and visual analytics methods on the business and social datasets. Our main finding is a clear link between negative sentiment and commercials. Despite positive change in customer behaviour, there was a negative change in customer opinion. Based on media events and broadcaster theories, we identify generalisable findings for all such transitions.

  • Platforms for big data analytics: Trend towards hybrid era

    The primary objective of this paper is to present detailed analysis of various platforms suitable for Big Data processing. In this paper, various software frameworks available for Big Data analytics are surveyed and in-detail assessment of their strengths and weaknesses is discussed. In addition to this, widely used data mining algorithm are discussed for their adaptation for Big Data analysis w.r.t their suitability for handling real-world application problems. Future trends of Big Data processing and analytics can be predicted with effective implementation of these well established and widely used data mining algorithms by considering the strengths of software frameworks and platforms available. Hybrid approaches (integration of two or more platforms) may be more appropriate for a specific data mining algorithm and can be highly adaptable as well as perform real-time processing.

  • Execution Models for Mobile Data Analytics

    Execution models enable mobile data analytics applications to run on multiple platforms, but these applications need to handle massive heterogeneity. This article discusses various options for designing execution models and presents related challenges.

  • INTERNET OF THINGS AND DATA ANALYTICS IN THE CLOUD WITH INNOVATION AND SUSTAINABILITY

    Big data analytics and machine learning provide intelligence and play a pivotal role in driving Internet of Things (IoT) devices. This chapter introduces the fundamentals and anatomy of IoT and data analytics technologies. Within each group, different sectors and potential applications are suggested. It discusses creativity, invention, and innovation as well as disruptive innovation (DI) and considers_How to Solve It_to fuel new products and new processes in the IoT ecosystem. The IoT technology concentrates on two broad types of standards, namely, technology standards and regulatory standards related to security and privacy of data. The IoT is no longer a buzzword; it is a fact of life. The cycle starting from creativity to invention to innovation is a compulsory backbone to flourish products applying IoT technology. A cloud model consists of five essential characteristics: on‐demand self‐service, broad network access, resource pooling, rapid elasticity, and measured service.

  • TV ratings vs. social media engagement: Big social data analytics of the Scandinavian TV talk show Skavlan

    This paper explores the relationship between TV viewership ratings for Scandinavian's most popular talk show, Skavlan and public opinions expressed on its Facebook page. The research aim is to examine whether the activity on social media affects the number of viewers per episode of Skavlan, how the viewers are affected by discussions on the Talk Show, and whether this creates debate on social media afterwards. By analyzing TV viewer ratings of Skavlan talk show, Facebook activity and text classification of Facebook posts and comments with respect to type of emotions and brand sentiment, this paper identifes patterns in the users' real-world and digital world behaviour.

  • Presentation 12. inVideo — A novel big data analytics tool for video data analytics

    Video data is a major format of unstructured data, and should be an indispensable area of big data analytics. Existing search engines and data analytics tools such as Google, SAS, SPSS and Hadoop are effective only in analyzing text and image data. Video data analytics are often neglected due to the complexity and challenges in penetrating into videos. In this presentation, we present a novel tool - inVideo for video data analytics. InVideo is able to analyze video content automatically without the need for the initial viewing by human. Using a highly efficient video indexing engine we developed, the system is able to analyze both language and video frames. The index engine identifies both keywords in the audio and objects or individuals in each frame based on reference files, pictures or knowledge. The time-stamped commenting and tagging features make it an effective tool for increasing interactions in online learning and social networking systems. During the presentation, we will demo how the automatic indexing algorithm works in indexing videos. We will also show how the search engine is able to search videos by keywords; by reference files using the Content-Based Image Retrieval (CBIR) algorithm; by knowledge using the knowledge tree we defined; and search videos with different languages. We will also demo how the collaborating filtering works by leveraging user feedback and in improving search engine accuracy. Tagging is another implementation on inVideo system. Videos with identical tags can be linked together or “cropped” based on the preferences. Learning is an integration of interaction. Tagging can turn a non-interactive linear video into an interactive video. This is vital in assessing interactions and outcomes in online learning and systems and MOOCs. We tested the inVideo system in an online learning environment. As longer videos are less likely to be viewed, we broke up the large videos into a serious of 3-5 minutes video clips using inVideo tool. As a result, the interactions in online classes increased seven folds across 24 classes we tested. Experiments also show that inVideo presents an efficient tool in improving interactions in online learning. We plan to expand the experiments in other areas for further studies.

  • Forecasting Nike's sales using Facebook data

    This paper tests whether accurate sales forecasts for Nike are possible from Facebook data and how events related to Nike affect the activity on Nike's Facebook pages. The paper draws from the AIDA sales framework (Awareness, Interest, Desire, and Action) from the domain of marketing and employs the method of social set analysis from the domain of computational social science to model sales from Big Social Data. The dataset consists of (a) selection of Nike's Facebook pages with the number of likes, comments, posts etc. that have been registered for each page per day and (b) business data in terms of quarterly global sales figures published in Nike's financial reports. An event study is also conducted using the Social Set Visualizer (SoSeVi). The findings suggest that Facebook data does have informational value. Some of the simple regression models have a high forecasting accuracy. The multiple regressions have a lower forecasting accuracy and cause analysis barriers due to data set characteristics such as perfect multicollinearity. The event study found abnormal activity around several Nike specific events but inferences about those activity spikes, whether they are purely event-related or coincidences, can only be determined after detailed case-by-case text analysis. Our findings help assess the informational value of Big Social Data for a company's marketing strategy, sales operations and supply chain.

  • Social network data analytics for market segmentation in Indonesian telecommunications industry

    Understanding market segmentation is a crucial aspect for business organizations to survive in high competitive environment. Traditional approach relies on sampling methodologies to gather demographic and other specific properties of market segment is considered expensive. The need of real-time decision making force us to adopt the new approach, which is taking advantage of social media data. In this paper, we investigate the conversation about specific product of telecommunication industry in social media Twitter. We use social network analysis methodology to identify group formation based on those conversations. By using social network to perform data analytics activities, we call our approach as Social Network Data Analytics based on community detection methods. Our result will show how many group formed, how many actors involved on each group, and with qualitative analysis we also have knowledge about the topics on each group formed and the attitude toward product.



Standards related to Data Analytics

Back to Top

No standards are currently tagged "Data Analytics"


Jobs related to Data Analytics

Back to Top