Theme: Emerging Future Technologies of Big Data and Data Mining

OMICS International is one of the leading Open Access publishers and organizers of international scientific conferences and events around the world. OMICS Group has so far organized 300+ International Conferences across the World and is managing 500+ peer-reviewed open access journals in basic science, health, and technology. OMICS International is also in association with more than 1000 International scientific and technological societies and associations.

Success Story

The success of the International Conference on Big Data Analysis and Data Mining  conference series has given us the prospect to bring the gathering one more time for our 2nd International Conference on Big Data Analysis and Data Mining. The highly exalted International conference on Data Mining hosted by OMICS International was marked with the attendance of young and brilliant researchers, business delegates and talented student communities representing more than 20 countries around the world. The conference has tried grounding every aspect related to Data Mining, covering all the possible research areas and crux. Awareness of Data Mining and its application is becoming popular among the general population. Parallel offers of hope add woes to the researchers of Data Mining due to the potential limitations experienced in the real-time.

OMICS International cordially invites all participants across the globe to attend the 2nd International Conference on Big Data Analysis and Data Mining (Data Mining-2015) which is going to be held during November 30 - December 2 in San Antonio, USA to share the advancements in the field of Data Mining and technology. The main theme of the conference is “Emerging Future Technologies of Big Data and Data Mining". This conference aimed to expand its coverage in the areas of Data Mining where expert talks, young researchers presentations will be placed in every session of the meeting will be inspired and keep up your enthusiasm. We feel our expert Organizing Committee is our major asset, however your presence over the venue will add one more feather to the crown of Data Mining-2015.

The Big data market has been achieving strong revenues. The Global Market Statistics shows that it has reached a revenue height of 7.39 USD (billion), 7.15 USD (billion) and 4.12 USD (billion) for services, hardware and software, respectively for the year 2013. The global market statistic also shows a revenue forecast for the global big data market from 2011 to 2017. For 2016, the source projects the global big data market is predicted to grow to more than 45 billion U.S. dollars in revenue.

Scientific Session

Session:1

Data Mining Methods and Algorithms: Data mining methods and algorithms an interdisciplinary subfield of computer science is the computational process of discovering patterns in large data sets involving methods like Big Data Search and Mining, Novel Theoretical Models for Big Data, New Computational Models for Big Data, High performance data mining algorithms, Methodologies on large-scale data mining, Methodologies on large-scale data mining, Big Data Analysis, Data Mining Analytics, Big Data and Analytics. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.Aside from the raw analysis step, it involves database and data management aspects, data pre- processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.

Session:2

Data Mining Tasks and Processes: Data mining task can be specified in the form of a data mining query. A data mining query is defined in terms of data mining task primitives. This track includes Competitive analysis of mining algorithms, Computational Modeling and Data Integration, Semantic-based Data Mining and Data Pre-processing, Mining on data streams, Graph and sub-graph mining, Scalable data preprocessing and cleaning techniques, Statistical Methods in Data Mining, Data Mining Predictive Analytics.

Session:3

Data Mining Applications in Science, Engineering, Healthcare and Medicine: Data Mining Applications in Engineering and Medicine targets to help data miners who wish to apply different data mining techniques. These applications include Data mining systems in financial market analysis, Application of data mining in education, Data mining and processing in bioinformatics, genomics and biometrics, Advanced Database and Web Application, Medical Data Mining, Data Mining in Healthcare, Engineering data mining, Data Mining in security, Social Data Mining, Neural Networks and Data Mining, these are some of the applications of datamining.

Session:4

Big Data Applications: Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Applications of bigdata include Big Data Analytics in Enterprises, Big Data Trends in Retail, Big Data in Travel Industry, Current and future scenario of Big Data Market, Financial aspects of Big Data Industry, Big data in clinical and healthcare, Big data in Regulated Industries, Big data in Biomedicine, Multimedia and Personal Data Mining.

Session:5

Data Mining Tools and Softwares: Data Mining tools and softwares include Big Data Security and Privacy, E-commerce and Web services, Medical informatics, Visualization Analytics for Big Data, Predictive Analytics in Machine Learning and Data Mining, Interface to Database Systems and Software Systems.

Session:6

Data Warehousing: In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis. Data Warehousing are central repositories of integrated data from one or more disparate sources. This data warehousing includes Data Warehouse Architectures, Case studies: Data Warehousing Systems, Data warehousing in Business Intelligence, Role of Hadoop in Business Intelligence and Data Warehousing, Commercial applications of Data Warehousing, Computational EDA (Exploratory Data Analysis) Techniques, Machine Learning and Data Mining.

Session:7

Artificial Intelligence: Artificial intelligence (AI) is the intelligence exhibited by machines or software.AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other.It includes Cybernetics, Artificial creativity, Artificial Neural networks, Adaptive Systems, Ontologies and Knowledge sharing.

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