Cognitive Computing: Where Big Data Is Driving Us

The integration of two of the biggest giants in the computing world has resulted in the development and advancement of new methodologies in data processing. Cognitive computing and big data analytics are integrated to give rise to advanced technologically sound algorithms like MOIWO and NSGA. There is an important role played by the E-projects portfolio selection (EPPS) issue in the web development environment that is handled with the help of a decision making algorithm based on big data. The EPPS problem tackles choosing the right projects for investment on the social media in order to achieve maximum return at minimal risk conditions. In order to address this issue and further optimize EPPS probe on social media, the proposed work focuses on building a hybrid algorithm known as NSGA-II-MOIWO. This algorithms makes use of the positive aspects of MOIWO algorithm and NSGA-II algorithm in order to develop an efficient one. The experimental results are recorded and analyzed in order to determine the most optimal algorithm based on the return and risk of investment. Based on the results, it is found that NSGA-II-MOIWO outperforms both MOIWO and NSGA, proving to be a better hybrid alternative.

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Big Data and Data Analytics Research

Web Services ◽

10.4018/978-1-5225-7501-6.ch112 ◽

2019 ◽

pp. 2161-2171

Author(s):

Miltiadis D. Lytras ◽

Vijay Raghavan ◽

Ernesto Damiani

Keyword(s):

Decision Making ◽

Big Data ◽

Data Analytics ◽

Business Models ◽

Internet Technology ◽

Cognitive Computing ◽

New Paradigm ◽

Web Science ◽

New Business ◽

Value Propositions

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.

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Predictive Analysis for Digital Marketing Using Big Data

Advances in Business Information Systems and Analytics - Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence ◽

10.4018/978-1-5225-2031-3.ch016 ◽

2017 ◽

pp. 259-283

Author(s):

Balamurugan Balusamy ◽

Priya Jha ◽

Tamizh Arasi ◽

Malathi Velu

Keyword(s):

Artificial Intelligence ◽

Social Media ◽

Big Data ◽

Statistical Analysis ◽

Data Analytics ◽

Big Data Analytics ◽

Predictive Analysis ◽

Cognitive Computing ◽

Internet Resources ◽

To Come

Big data analytics in recent years had developed lightning fast applications that deal with predictive analysis of huge volumes of data in domains of finance, health, weather, travel, marketing and more. Business analysts take their decisions using the statistical analysis of the available data pulled in from social media, user surveys, blogs and internet resources. Customer sentiment has to be taken into account for designing, launching and pricing a product to be inducted into the market and the emotions of the consumers changes and is influenced by several tangible and intangible factors. The possibility of using Big data analytics to present data in a quickly viewable format giving different perspectives of the same data is appreciated in the field of finance and health, where the advent of decision support system is possible in all aspects of their working. Cognitive computing and artificial intelligence are making big data analytical algorithms to think more on their own, leading to come out with Big data agents with their own functionalities.

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Big Data-Driven Cognitive Computing System for Optimization of Social Media Analytics

IEEE Access ◽

10.1109/access.2020.2991394 ◽

2020 ◽

Vol 8 ◽

pp. 82215-82226 ◽

Cited By ~ 6

Author(s):

Arun Kumar Sangaiah ◽

Alireza Goli ◽

Erfan Babaee Tirkolaee ◽

Mehdi Ranjbar-Bourani ◽

Hari Mohan Pandey ◽

...

Keyword(s):

Social Media ◽

Big Data ◽

Computing System ◽

Data Driven ◽

Social Media Analytics ◽

Cognitive Computing

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Cognitive Intelligence

International Journal of Cognitive Informatics and Natural Intelligence ◽

10.4018/ijcini.2016100101 ◽

2016 ◽

Vol 10 (4) ◽

pp. 1-20 ◽

Cited By ~ 40

Author(s):

Yingxu Wang ◽

Bernard Widrow ◽

Lotfi A. Zadeh ◽

Newton Howard ◽

Sally Wood ◽

...

Keyword(s):

Machine Learning ◽

Big Data ◽

Computational Intelligence ◽

Cognitive Systems ◽

Cognitive Computing ◽

Cognitive Intelligence ◽

Basic Studies ◽

Deep Reasoning ◽

Intelligence Theories ◽

The Brain

The theme of IEEE ICCI*CC'16 on Cognitive Informatics (CI) and Cognitive Computing (CC) was on cognitive computers, big data cognition, and machine learning. CI and CC are a contemporary field not only for basic studies on the brain, computational intelligence theories, and denotational mathematics, but also for engineering applications in cognitive systems towards deep learning, deep thinking, and deep reasoning. This paper reports a set of position statements presented in the plenary panel (Part I) in IEEE ICCI*CC'16 at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

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