scholarly journals Interactive Marketing E-Commerce Recommendation System Driven by Big Data Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yi Fu ◽  
Min Yang ◽  
Di Han
Keyword(s):  
Big Data ◽  
Recommendation System ◽  
Reference Model ◽  
Relevant Literature ◽  
Force Model ◽  
Interactive Marketing ◽  
Marketing Innovation ◽  
Interactive Relationship ◽  
The Media ◽  
Big Data Technology

This study combs through relevant literature, adopts a combination of typical sampling and random sampling, collects three big data technology-driven interactive marketing e-commerce companies in a specific period of Sina Weibo sample data for research, obtains historical information and data, and constructs a model. Through relevant analysis to eliminate invalid variables, we creatively selected three variables of Internet hot words, activities, and microtopics as independent variables and used marketing effects as dependent variables to carry out empirical analysis and study the marketing innovation of three representative companies based on big data technology. We discussed the use of self-media in interactive marketing e-commerce and the situation of marketing innovation based on self-media, focusing on the interactive relationship between marketing innovation and Internet word-of-mouth (brand image). Through research, we have derived the three-force model, which is the biggest result of this research, and provided a reference model for interactive marketing e-commerce companies to carry out follow-up marketing innovation based on the media. Limited to the level of research and ability, there are some deficiencies in the research, such as barrage marketing, big data marketing, and emotional computing, that have not been analyzed in depth. This article fully considers the dependence of small and medium e-commerce companies on e-commerce platforms in the era of big data and conducted detailed market research on their precision marketing strategies in the era of big data. This will be a new field that does not come from media marketing. This article intends to summarize a series of experiences and laws from special to general, from individuality to generality, so as to give full play to the role of personalized marketing in increasing website traffic and order conversion, in order to personalize the use of data by other e-commerce companies with marketing provides some valuable experiences and methods for reference.

scholarly journals Mediatisation as a Driver of Big Data Growth

2020 ◽  
Author(s):  
Ekaterina Gribovod ◽  
Keyword(s):  
Big Data ◽  
New Media ◽  
Secondary Data ◽  
Social Institutions ◽  
Heterogeneous Data ◽  
Technical Aspect ◽  
Theoretical Concept ◽  
Media Space ◽  
The Media ◽  
Big Data Technology

The possibilities and consequences of the application and penetration of information technology in different spheres of society are of particular interdisciplinary interest in today’s academic environment. The methodological basis of the study was a combination of informational, comparative, systematic and conceptual approaches. Besides that, the secondary data analysis method was employed. This article examines mediatisation as an important factor in accelerating the accumulation of big data in the digital age. With the emergence of new media and the digitalisation of modern media space, researchers have recorded a process of ‘deep mediatisation’. It is noted that, in domestic practice, the main emphasis in the study of the phenomenon of ‘Big Data’ is on its technical aspect, while socio-humanitarian characteristics and effects are revealed to a lesser extent. The article represents an attempt to consider ‘Big Data’ technology as a symbolic and authoritative resource of the information society. Mediatisation and big data are interrelated. On one hand, ‘Big Data’ technology allows for the identification and measurement of quantitative indicators of the mediatisation process (e.g. active social media audience, etc.) and facilitates the processing of the findings. Mediatisation, on the other hand, facilitates the accumulation of heterogeneous data and, as a theoretical concept, allows for the implications of big data technology to be identified and for social institutions to be adapted to it. In addition, mediatisation is changing the paradigm of the private and individual aspects in media space as a result of the growth in the volume, storage and reproduction of social information in the digital society, the lowering of the barrier of access to the media age, and the emergence of new actors of communication: micro-subjects (e.g. Influencers).

scholarly journals Research on XBRL Continuous Internal Audit under the Big Data

2021 ◽  
Vol 2050 (1) ◽  
pp. 012016
Author(s):  
Yong Wen
Keyword(s):  
Big Data ◽  
Relevant Literature ◽  
Digital Technologies ◽  
Internal Audit ◽  
Internal Auditing ◽  
Audit Process ◽  
New Models ◽  
Important Means ◽  
The Impact ◽  
Big Data Technology

Abstract The development of digital industrialization has promoted the continuous emergence of new industries, new formats and new models, and has also promoted the transformation of the traditional internal audit model to digital and intelligent. Big data, cloud computing, XBRL, artificial intelligence and other digital technologies are important means to achieve full audit coverage, big data audit has become a hot topic in the current audit field, relevant literature mainly focuses on the impact of big data on traditional audit concepts and audit methods, the impact and risks of big data technology on informatization audits, and how the auditing community responds. However, the research on the integration of big data technology and XBRL technology into continuous internal auditing is relatively rare. Based on the introduction of three XBRL continuous internal audit models, this article analyzes the continuous internal audit process of the XBRL information system, and discusses the application of big data technology in XBRL continuous internal audit.

scholarly journals Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
HongYan Liang
Keyword(s):  
Big Data ◽  
Recommendation System ◽  
Contextual Information ◽  
Clustering Algorithms ◽  
Personalized Recommendation ◽  
Information Usage ◽  
Practical Effect ◽  
Tourism Information ◽  
Travel Recommendation ◽  
Big Data Technology

Actual tourism mining models are often used to discover potential information in documents, but tourism models without human knowledge often produce unexplainable topics. This paper combines big data technology to build a personalized recommendation system for smart tourism, model the contextual information usage ontology under the tourism information system, and give the association between various ontologies. Then, this paper uses a matrix to describe each discrete attribute and interval attribute and uses a vector to model the user’s preferences. In addition, this paper constructs an intelligent recommendation system based on the actual needs of travel recommendation and verifies the system in combination with experimental research. Through experimental analysis, it can be known that the intelligent tourism personalized recommendation system based on big data technology proposed in this paper has a high practical effect.

scholarly journals STUDI IMPLEMENTASI SISTEM BIG DATA UNTUK MENDUKUNG KEBIJAKAN KOMUNIKASI DAN INFORMATIKA

2018 ◽  
Vol 8 (2) ◽  
pp. 81
Author(s):  
Dita Kusumasari ◽  
Onny Rafizan
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Implementation Process ◽  
Time Cost ◽  
Require Time ◽  
The Media ◽  
Promising Solution ◽  
Process Variety ◽  
Short Time ◽  
Big Data Technology

AbstractMedia Monitoring became one of the tasks and functions of the Ministry of Communications and Information Technology, in accordance with Presidential Instruction No. 9/2015. The process should be done in short time while maintaining or even improving the accuracy of analysis of the media. Therefore Big Data technology becoming a promising solution, related abilities of Big Data to process variety of data in a large scale, also provide accurate reports for stakeholders. This study adopted the Modified Waterfall method that commonly used in manufacture of software. This method is expected to explores and creates an appropriate recommendation. Big Data Implementation process will require time, cost, and human resources, so that stakeholders and related user is expected to prepare the implementation process properly in order to be effective. AbstrakMonitoring media menjadi salah satu tugas dan fungsi Kementerian Komunikasi dan Informatika, sesuai dengan Instruksi Presiden No. 9 Tahun 2015. Proses dalam monitoring media tersebut harus dapat diselesaikan dalam waktu cepat tanpa mengurangi akurasi dari analisis terhadap media tersebut. Oleh karena itu teknologi Big Data menjadi salah satu solusi yang menjanjikan, terkait sifatnya yang mampu mengolah data dalam skala yang sangat besar dan variatif serta menyajikan laporan yang akurat untuk digunakan oleh pemangku kebijakan. Penelitian ini mengadopsi metode Modified Waterfall yang biasa digunakan dalam pembuatan software. Metode ini diharapkan dapat mendalami, mengeksplorasi dan menghasilkan alternatif rekomendasi yang sesuai. Proses pengimplementasian Big Data akan membutuhkan biaya, SDM, dan waktu yang tidak sedikit, sehingga pemangku kebijakan dan user terkait diharapkan dapat lebih mempersiapkan dengan baik agar proses pengimplementasian dapat berjalan efektif dan maksimal.

A New Rockburst Experiment Data Compression Storage Algorithm based on Big Data Technology

2019 ◽  
pp. 561-573
Author(s):  
Yu Zhang ◽  
Yan-Ge Wang ◽  
Yan-Ping Bai ◽  
Yong-Zhen Li ◽  
Zhao-Yong Lv ◽  
...  
Keyword(s):  
Big Data ◽  
Data Compression ◽  
Experiment Data ◽  
Big Data Technology

scholarly journals Validity of the “Big Data Tendency in Education” Scale as a Tool Helping to Reach Inclusive Social Development

2020 ◽  
Vol 12 (13) ◽  
pp. 5470 ◽  
Author(s):  
Antonio Matas-Terrón ◽  
Juan José Leiva-Olivencia ◽  
Pablo Daniel Franco-Caballero ◽  
Francisco José García-Aguilera
Keyword(s):  
Big Data ◽  
Inclusive Education ◽  
Sustainable Development Goals ◽  
Sustainable Society ◽  
Education Students ◽  
The Sustainable Development ◽  
Research Goal ◽  
Development Goals ◽  
Nonprobability Sample ◽  
Big Data Technology

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.

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