scholarly journals Webliometric Indicators as Elements of the AI Technique of Estimation of the Language Teacher’s Net Proficiency

2021 ◽  
Author(s):  
Matukhin Pavel ◽  
Provotorova Elena ◽  
Petrova Marina ◽  
Gracheva Olga ◽  
Rybakova Irina ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Language Teachers ◽  
Initial Information ◽  
Internet Resources ◽  
Wide Range ◽  
Search Systems

The article deals with the issues related to the scientometric indexing of the net resources of the group of language teachers and scientists. A detailed accounting of all types of publications allows us to obtain initial information about the level of their Internet engagement. The analysis was carried out including a wide range of genres of publications, the structure of publications, the format and language of publications, the corpus of academic subjects, the language aspects of the publications under study, the composition of the authors of publications, based on their position. The authors’ use of wide opportunities to present their developments on various Internet resources provides them with the opportunity to be detected by search systems based on artificial intelligence (AI) as well as Big Data techniques and to be most fully characterized by existing and prospective scientometric systems.

Predictive Analysis for Digital Marketing Using Big Data

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.

Big Data, Artificial Intelligence, and the Internet of Things in Cross-Border E-Commerce

2021 ◽  
pp. 257-272
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Economic Globalization ◽  
The Internet ◽  
Technological Revolution ◽  
Cross Border ◽  
Wide Range ◽  
The Internet Of Things

Today, the terms big data, artificial intelligence, and internet of things (IoT) are many-fold as these are linked with various applications, technologies, eco-systems, and services in the business domain. The recent industrial and technological revolution have become popular ever before, and the cross-border e-commerce activities are emerging very rapidly. As a result, it supports to the growth of economic globalization that has strategic importance for the advancement of e-commerce activities across the globe. In the business industry, the wide range applications of technologies like big data, artificial intelligence, and internet of things in cross-border e-commerce have grown exponential. This chapter systematically reviews the role of big data, artificial intelligence, and IoT in cross-border e-commerce and proposes a conceptually-designed smart-integrated cross-border e-commerce platform.

scholarly journals Alkalmazott mesterséges intelligencia felhasználási területei és biztonsági kérdései – Mesterséges intelligencia a gyakorlatban

2020 ◽  
Vol 1 (1) ◽  
pp. 35-42
Author(s):  
Péter Ekler ◽  
Dániel Pásztor
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Anomaly Detection ◽  
Real Time ◽  
Learning Algorithm ◽  
Sensor Data ◽  
Test Field ◽  
Real Time System ◽  
Data Set ◽  
Wide Range

Összefoglalás. A mesterséges intelligencia az elmúlt években hatalmas fejlődésen ment keresztül, melynek köszönhetően ma már rengeteg különböző szakterületen megtalálható valamilyen formában, rengeteg kutatás szerves részévé vált. Ez leginkább az egyre inkább fejlődő tanulóalgoritmusoknak, illetve a Big Data környezetnek köszönhető, mely óriási mennyiségű tanítóadatot képes szolgáltatni. A cikk célja, hogy összefoglalja a technológia jelenlegi állapotát. Ismertetésre kerül a mesterséges intelligencia történelme, az alkalmazási területek egy nagyobb része, melyek központi eleme a mesterséges intelligencia. Ezek mellett rámutat a mesterséges intelligencia különböző biztonsági réseire, illetve a kiberbiztonság területén való felhasználhatóságra. A cikk a jelenlegi mesterséges intelligencia alkalmazások egy szeletét mutatja be, melyek jól illusztrálják a széles felhasználási területet. Summary. In the past years artificial intelligence has seen several improvements, which drove its usage to grow in various different areas and became the focus of many researches. This can be attributed to improvements made in the learning algorithms and Big Data techniques, which can provide tremendous amount of training. The goal of this paper is to summarize the current state of artificial intelligence. We present its history, introduce the terminology used, and show technological areas using artificial intelligence as a core part of their applications. The paper also introduces the security concerns related to artificial intelligence solutions but also highlights how the technology can be used to enhance security in different applications. Finally, we present future opportunities and possible improvements. The paper shows some general artificial intelligence applications that demonstrate the wide range usage of the technology. Many applications are built around artificial intelligence technologies and there are many services that a developer can use to achieve intelligent behavior. The foundation of different approaches is a well-designed learning algorithm, while the key to every learning algorithm is the quality of the data set that is used during the learning phase. There are applications that focus on image processing like face detection or other gesture detection to identify a person. Other solutions compare signatures while others are for object or plate number detection (for example the automatic parking system of an office building). Artificial intelligence and accurate data handling can be also used for anomaly detection in a real time system. For example, there are ongoing researches for anomaly detection at the ZalaZone autonomous car test field based on the collected sensor data. There are also more general applications like user profiling and automatic content recommendation by using behavior analysis techniques. However, the artificial intelligence technology also has security risks needed to be eliminated before applying an application publicly. One concern is the generation of fake contents. These must be detected with other algorithms that focus on small but noticeable differences. It is also essential to protect the data which is used by the learning algorithm and protect the logic flow of the solution. Network security can help to protect these applications. Artificial intelligence can also help strengthen the security of a solution as it is able to detect network anomalies and signs of a security issue. Therefore, the technology is widely used in IT security to prevent different type of attacks. As different BigData technologies, computational power, and storage capacity increase over time, there is space for improved artificial intelligence solution that can learn from large and real time data sets. The advancements in sensors can also help to give more precise data for different solutions. Finally, advanced natural language processing can help with communication between humans and computer based solutions.

RESEARCH ON THE CONSTRUCTION OF A NEW SMART CITY IN HUZHOU (CHINA)

2021 ◽  
pp. 25-29
Author(s):  
Menglin Xu
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Living Environment ◽  
Scientific Management ◽  
City Management ◽  
Starting Point ◽  
Wide Range ◽  
Countermeasures And Suggestions

Taking solving urban problems and serving urban development as the starting point, smart city comprehensively uses information technology means such as big data, network communication, artificial intelligence and satellite remote sensing to solve population, resource and environmental problems in combination with scientific management methods. It is a new intelligent city model proposed to promote urban health, safety and sustainable development. Through the background of smart city, focusing on the core issues such as what is a smart city, what kind of smart city to build and how to build a smart city, and based on the analysis and investigation of the development status of the smart city in Huzhou, this paper analyzes and expounds the problems existing in the construction of the smart city in Huzhou, This paper puts forward the countermeasures and suggestions to promote the development of the new smart city in Huzhou City. It gives information on further development within the proper implementation of the smart city concept. Firstly, this concept needs a wide range of specialists in the field of management, informatics, geography, architecture, regional economy, who should work in close cooperation synergistically. Secondly, it is substantial to applicate new technologies, for instance, they can be cloud computing, big data, GIS, the Internet of Things and artificial intelligence, etc. The current state of construction of a smart city is emphasized in unsatisfactory condition, hence, the development of the smart city in Huzhou needs all of the above factors. In the light of all evidence, to further develop a smart city, a set of measures is recommended, including clarifying development goals and providing scientific assistance to construction, providing smart planning, strengthening leadership and introduction of new technologies, establishing communications to explain the concept of building a smart city. Such a city will have convenient public services, improved city management, a proper living environment, well-developed intellectual infrastructure and long-term network security.

scholarly journals The Revolution of Artificial Intelligence and the Significance of Adopting AI in different Industries

2019 ◽  
Vol 8 (4S2) ◽  
pp. 642-644
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Learning Technologies ◽  
Large Sets ◽  
Wide Range ◽  
Data Points ◽  
Machine Interaction ◽  
The Revolution

Artificial Intelligence (AI) is one of the most widely inflated technologies in several industries today. With the emergence of IoT, Big data and Digitalization, many industries produce large sets of data and AI begins to be the prominence for solving the increasing number of complications in this relevance. Artificial Intelligence (AI) and Machine Learning (ML) applications, spectacle substantial guarantee in gaining commercial traction in several businesses as AI brings with a probable of genuine human-to-machine interaction. When machines become intelligent, they can understand needs, connect with data points and arrive at better decisions. Therefore, Artificial Intelligence (AI) and Machine Learning technologies are being quickly adopted in wide range of applications in several industries. In this paper, we epitomize the fundamentals and the significance of adopting of Artificial Intelligence technologies in different industries.

Predictive Analysis for Digital Marketing Using Big Data

Web Services ◽  
2019 ◽  
pp. 745-768
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.

scholarly journals Big Data, artificial intelligence and the geography of entrepreneurship in the United States

2018 ◽  
Author(s):  
Martin Obschonka ◽  
Neil Lee ◽  
Andrés Rodríguez-Pose ◽  
johannes Christopher Eichstaedt ◽  
Tobias Ebert
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Big Five ◽  
The United States ◽  
Economic Outcomes ◽  
Entrepreneurial Activity ◽  
Personality Profile ◽  
Artificial Intelligence Methods ◽  
Wide Range

There is increasing interest in the potential of artificial intelligence and Big Data (e.g., generated via social media) to help understand economic outcomes and processes. But can artificial intelligence models, solely based on publicly available Big Data (e.g., language patterns left on social media), reliably identify geographical differences in entrepreneurial personality/culture that are associated with entrepreneurial activity? Using a machine learning model processing 1.5 billion tweets by 5.25 million users, we estimate the Big Five personality traits and an entrepreneurial personality profile for 1,772 U.S. counties. We find that these Twitter-based personality estimates show substantial relationships to county-level entrepreneurship activity, accounting for 20% (entrepreneurial personality profile) and 32% (all Big Five trait as separate predictors in one model) of the variance in local entrepreneurship and are robust to the introduction in the model of conventional economic factors that affect entrepreneurship. We conclude that artificial intelligence methods, analysing publically available social media data, are indeed able to detect entrepreneurial patterns, by measuring territorial differences in entrepreneurial personality/culture that are valid markers of actual entrepreneurial behaviour. More importantly, such social media datasets and artificial intelligence methods are able to deliver similar (or even better) results than studies based on millions of personality tests (self-report studies). Our findings have a wide range of implications for research and practice concerned with entrepreneurial regions and eco-systems, and regional economic outcomes interacting with local culture.

scholarly journals Artificial Intelligence– Electronic Medical Records Framework to predict COVID-19 by using Wearable IoT Devices

2020 ◽  
Vol 9 (4) ◽  
pp. 89-91
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Respiratory Infections ◽  
Wide Range ◽  
Difficulty Breathing ◽  
Iot Devices ◽  
The Cost ◽  
Improving Patient Care

Corona virus is an infectious disease that causes respiratory infections, producing fever, difficulty breathing, and dry cough, which may be more dangerous for people who suffer from chronic diseases. Wearable Devices (WD) have been recently adopted in a wide range of areas to show distinct potentials in the healthcare field. The different types of WDs can be one of the important steps towards improving patient care while reducing the cost based on artificial intelligence (AI) applications. These applications work on big data that arise from WDs despite the existence of various challenges such as user acceptance, security, ethics issues, big data, AI and interoperability. The purpose of this study is to drawthe possibility of utilizing the big data arising from integrating WDs with the electronic Medical records (EMR) through applying AI technologies which in turn will lead to the possibility of employing all of these technologies in predicting COVID-19 infection

scholarly journals A New World Post COVID-19

2020 ◽  
Author(s):  
Monica Billio ◽  
Simone Varotto
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Monetary Policy ◽  
Big Data ◽  
Financial Markets ◽  
New World ◽  
Policy Makers ◽  
Wide Range ◽  
Change Labour Market ◽  
Fiscal And Monetary Policy

Pandemics are disruptive events that have profound consequences for society and the economy. This volume aims to present an analysis of the economic impact of COVID-19 and its likely consequences for our future. This is achieved by drawing from the expertise of authors who specialise in a wide range of fields including fiscal and monetary policy, banking, financial markets, pensions and insurance, artificial intelligence and big data, climate change, labour market, travel, tourism and politics, among others. We asked contributing authors to write their chapters for a non-technical audience so that their message could reach beyond academia and professional economists to policy makers and the wider society. The material in this volume draws from the latest research and provides a wealth of ideas for further investigations and opportunities for reflection. This also makes it an ideal learning tool for economics and finance students wishing to gain a deeper understanding of how COVID-19 could influence their disciplines.

scholarly journals On the logic-game approach to the problems of working with big data

2021 ◽  
Author(s):  
Roman Viktorovich Khelemendik
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Organization Of Work ◽  
Wide Range

When working with big data, the problems of search, presentation, systematization, updating, analysis of information, application of artificial intelligence, communication, verification and understanding of conclusions are considered. Examples of solutions to some aspects of these problems, shown in the organization of work with information in chess, are given. The so-called logic-game approach is proposed, which provides ways to adapt and formalize solutions for a fairly wide range of problems with big data.

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