scholarly journals Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data

2020 ◽  
Vol 12 (8) ◽  
pp. 3381
Author(s):  
Yingyan Zhao ◽  
Yihong Zhou ◽  
Wu Deng
Keyword(s):  
Big Data ◽  
Business Processes ◽  
Rapid Development ◽  
Influence Factors ◽  
Route Optimization ◽  
Internet Technology ◽  
Optimization Strategy ◽  
Logistics Distribution ◽  
Low Efficiency ◽  
Distribution Efficiency

With the advent of big data era and rapid development of Internet technology, e-commerce has had a strong development tendency that causes many problems, such as redundant and complex business processes, low efficiency and a high cost for e-commerce logistics in the distribution sector. It is not difficult to conclude that the key to improving logistics distribution efficiency—and reduce logistics distribution costs—is to optimize logistics distribution under big data. In this study, the management model, influence factors and development status of B2C e-commerce logistics distribution under big data are analyzed in detail. Then big data processing, business process and route optimization strategies for B2C e-commerce logistics distribution under big data are deeply studied. Furthermore, an optimization model of product sales and logistics distribution of B2C e-commerce by big data platform is discussed in order to propose an innovative optimization strategy for B2C e-commerce logistics distribution under big data. Big data technology is applied in B2C e-commerce logistics business management, which is studied in detail. These findings achieve the optimal distribution of B2C e-commerce, reduce the B2C e-commerce logistics distribution cost and improve the B2C e-commerce logistics distribution efficiency under big data. In addition, enhanced competitiveness of B2C e-commerce logistics distribution is examined in this study. This study provides a reference for follow-up big data studies in the field of e-commerce.

scholarly journals Smart City Rail Automatic Fare Collection System Under the Background of Big Data

2022 ◽  
Vol 2146 (1) ◽  
pp. 012013
Author(s):  
Shurun Xie
Keyword(s):  
Big Data ◽  
Smart City ◽  
System Development ◽  
Rapid Development ◽  
Response Speed ◽  
Fast Response ◽  
Internet Technology ◽  
Collection System ◽  
Human Material ◽  
Low Efficiency

Abstract With the rapid development of Internet technology, the process of urban construction is accelerating and the level of urbanization is further improved. In the smart city rail automatic fare collection system, there are a large number of data information and data that need to be processed manually. The traditional manual method not only consumes human, material and financial resources, but also has low efficiency. Therefore, this paper proposes a smart city rail automatic fare collection system based on big data design. Firstly, this paper expounds the concept of smart city rail transit and studies the function of automatic fare collection system. Then it studies the definition and characteristics of big data, designs the method of system development, and tests the performance of the system. The test results show that the system runs smoothly, accounts for a relatively small amount of memory, has a fast response speed and low delay. Most passengers are satisfied with the system.

Research on Database Schema Comparison of Relational Databases and Key-Value Stores

2014 ◽  
Vol 1049-1050 ◽  
pp. 1860-1863
Author(s):  
Peng Zhou ◽  
Mei Li ◽  
Jing Huang ◽  
Hua Fang
Keyword(s):  
Big Data ◽  
Relational Databases ◽  
Efficient Solution ◽  
Rapid Development ◽  
Internet Technology ◽  
Database Schema ◽  
Typical Application ◽  
Existing Problems ◽  
Management Capacity ◽  
High Scalability

With the rapid development of Internet technology, the management capacity of traditional relational databases becomes relatively inefficient when facing the access and processing of big data. As a kind of non-relational databases, the key-value stores, with its high scalability, provide an efficient solution to the problem. This article introduces the concept and features of Key-Value stores, and followed by the comparison with the traditional relational databases, and an example is illustrated to explain its typical application and finally the existing problems of Key-Value stores are summarized.

A Generic Model of an Enterprise Portal

2011 ◽  
pp. 419-424
Author(s):  
Xiuzhen Feng
Keyword(s):  
Information Management ◽  
Business Processes ◽  
Rapid Development ◽  
Internet Technology ◽  
Generic Model ◽  
Enterprise Information ◽  
Information Portal ◽  
Enterprise Collaboration ◽  
Enterprise Information Portal ◽  
Knowledge Portal

With the rapid development of Internet technology, the portal has been envisioned as one of the greatest opportunities to improve the management of enterprise information. A number of portals associated with enterprise information portal, e-market portal, business portal, enterprise collaboration portal, enterprise knowledge portal, enterprise portal or enterprise information portal, etc. As one of the most important applications of portals, an enterprise portal is more attractive because it could be used not only to improve information management and business processes management (Collins, 2002; Detlor, 2004; Terra & Gordon, 2003), but also to promote business collaborations and interactions both internally and externally (Dias, 2001; Detlor, 2000).

Improving the performance of precision poverty alleviation based on big data mining and machine learning

2020 ◽  
pp. 1-12
Author(s):  
Lejie Wang
Keyword(s):  
Machine Learning ◽  
Economic Growth ◽  
Big Data ◽  
Low Income ◽  
Large Scale ◽  
Rapid Development ◽  
Machine Learning Algorithms ◽  
Internet Technology ◽  
Rapid Economic Growth ◽  
Causes Of Poverty

Since the reform began in our country, with the rapid economic growth in recent years, the income level has grown extremely unequal, and it is difficult for the low-income poor to benefit from the rapid economic growth. The most important prerequisite for the fight against poverty is the accurate identification of the causes of poverty. To date, our country has not reached the level of maturity required to accurately study the causes of poverty in various households. However, with the rapid development of Internet technology and big data technology in recent years, the application of large-scale data technology and data extraction algorithms to poverty reduction can identify truly poor households faster and more accurately. Compared with traditional machine learning algorithms, there are no machine storage and technical constraints, can use a large amount of data and rely on multiple data samples.

scholarly journals Transportation route optimization based on heuristic algorithm

2021 ◽  
Vol 2083 (3) ◽  
pp. 032016
Author(s):  
Fan Wu ◽  
Yongan Zhu
Keyword(s):  
Heuristic Algorithm ◽  
Time Window ◽  
Rapid Development ◽  
Route Optimization ◽  
Internet Technology ◽  
Mixed Integer ◽  
Routing Problem ◽  
Freight Volume ◽  
Transportation Organization ◽  
Transportation Company

Abstract With the rapid development of Internet technology, many enterprises are committed to finding the best solution in transportation organization and solving the vehicle distribution routing problem. Firstly, this paper introduces the current situation of transportation organization of Sichuan Yida Feiniu Transportation Company, and analyzes the main problems of the company. Secondly, through the prediction of freight volume, prepare the truck vehicle operation plan and optimize the company’s transportation organization and production plan. Finally, the heuristic algorithm is used to establish a mixed integer programming mathematical model to optimize the pooled vehicle distribution path problem and the vehicle distribution path with time window. In terms of centralized vehicle distribution, combined with the actual situation of Sichuan Yida Feiniu Transportation Company, an example is analyzed, the shortest total path is obtained, and the goal of shortest vehicle travel distance is realized. Through the optimization of the company’s transportation organization, this paper is of great significance to improve the company’s transportation organization to a certain extent.

scholarly journals RESEARCH ON BEHAVIORAL MOTIVATION INFERENCE METHOD FOR GEOGRAPHICAL SPATIOTEMPORAL LARGE DATA

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 725-729
Author(s):  
J. W. Li ◽  
W. D. Chen ◽  
Y. Ma ◽  
N. Yu ◽  
X. Li ◽  
...  
Keyword(s):  
Big Data ◽  
Association Rules ◽  
User Behavior ◽  
Rapid Development ◽  
Frequent Itemsets ◽  
Internet Technology ◽  
Personalized Recommendation ◽  
User Interest ◽  
Geographic Context ◽  
Spatio Temporal

Abstract. Along with the rapid development of Internet technology, GNSS technology and mobile terminals, a large amount of information including geographical location and time attributes has been generated. Faced with large and complex Internet geospatial data, how to quickly and accurately extract valuable reference information becomes an urgent problem to be solved. And the user's demand for personalized information of recommendation information is getting stronger and stronger, and researching efficient and accurate personalized recommendation system has good application value. In this paper, based on the application requirements of personalized recommendation information, the GIS platform and related recommendation algorithms are used to fully exploit the user and location based on geographic space-time big dataIt is divided into user explicit interest and user implicit interest, and then establishes a scientific and efficient user behavior motivation prediction model based on geographic situation. User interest information can be obtained from explicit interest information, implicit interest information and geographic situation interest information. Geographical environment, geographic location and other related context information. By introducing time factors, it is used to update and improve the user real-time interest model to achieve accurate prediction of user behavior motives under geographic spatio-temporal big data. Use Apriori algorithm to calculate the support and determine the current Frequent itemsets of user interest in geographic context, using frequent itemsets to generate strong association rules, and realizing the analysis of user behavior motives based on geography context. For geographic spatio-temporal big data, this paper proposes a personalized hybrid recommendation algorithm, which is based on users. Effective combination of collaborative filtering algorithms and association rules for geographic context-user behavioral interest adaptation.

scholarly journals Application Strategy of Big Data Processing Technology in Intelligent Transportation

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Yaohua Xie ◽  
Xin Zhou
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Traffic Management ◽  
Traffic Accidents ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Processing Technology ◽  
Internet Technology ◽  
Big Data Processing ◽  
Artificial Intelligence Technology

With the rapid development of China’s society and economy, the process of urbanization has been accelerated, and the transportation system has become more complicated, especially the frequent occurrence of traffic accidents, traffic congestions, and environmental pollution. In the context of the rapid development of Internet technology, digital technology, artificial intelligence technology, etc. We apply them to traffic management as effective ways to improve China’s traffic operation management. Based on big data processing technology, this paper discusses its application strategy in intelligent transportation, in hope of serving as a reference.

scholarly journals A Refection on Digitalized Creation of Chinese Internet Big Movies in the Context of Internet

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Liang Lei ◽  
Kunhao Ni ◽  
Ying Cui
Keyword(s):  
Big Data ◽  
Rapid Development ◽  
Internet Technology ◽  
Production Model ◽  
The Internet ◽  
Artistic Creation ◽  
Chinese Film ◽  
Big Data Technologies ◽  
New Type ◽  
New Phenomena

The 21st century is the era of the Internet, where movies see new vitality in artistic creation under the concept of the Internet+. Internet Big movies, a new type of films born with the advancement of Internet technology, have seen rapid development in less than a decade, having gradually established a mature production model. This paper provides reflection and analysis on the new phenomena in Chinese film production that involve numerous applications of big data technologies.

scholarly journals On E-Commerce Precision Marketing Strategy Based on Big Data

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Yushui Xiao ◽  
Feng Ling
Keyword(s):  
Big Data ◽  
Marketing Strategy ◽  
Computer Technology ◽  
Market Competition ◽  
Rapid Development ◽  
Internet Technology ◽  
Purchasing Power ◽  
Current Development ◽  
Online Sales ◽  
Sales Model

Nowadays, Internet technology has been developed to a higher level, and has also gained more and more popularity in people's life and work. Internet technology has penetrated into many fields, providing more convenience for people. Judging from the current development momentum of China's e-commerce industry, fierce market competition and increasingly picky demand of customers, coupled with the gradual formation of online sales model, have all made the existing e-commerce industry face greater challenges, as well as opportunities worth taking advantage of. At present, relying on the rapid development of Internet and computer technology, the concept of "big data" has been popularized. Under the background of big data, every industry has undergone changes and improvement, especially the e-commerce industry, which can more accurately determine the consumers' consumption needs and habits, and can further understand their purchasing power, thus realizing accurate marketing, and strengthening its marketing reliability and pertinence.

scholarly journals Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ye Cheng ◽  
Yan Song
Keyword(s):  
Economic Development ◽  
Big Data ◽  
Data Analysis ◽  
Rapid Development ◽  
Information Age ◽  
Big Data Analysis ◽  
Internet Technology ◽  
Support Vector ◽  
Cloud Platform ◽  
The Impact

The service information system is constantly transforming to a networked information model, and domestic hardware equipment is constantly updated. Independent controllability has also become the basic requirement of the new information age. With the development of the information age and the new era of independent control, more and more services and applications will also be deployed on autonomous and controllable cloud platforms. With the rapid development of Internet technology in the information age and the resulting changes in productivity, people can record, store, and transmit more and more information. When information becomes recordable, storage, and easy to transmit, information becomes modern meaning nowadays, an era of information explosion characterized by massive, volatile, timely transmission, and diverse forms has truly come, forming what is now called the “big data era”. This article mainly introduces the analysis of sports big data based on the cloud platform and the research on the impact on the sports economy and intends to provide ideas and directions for the analysis of sports big data and the research on the impact on the sports economy. This paper proposes a cloud platform-based sports big data analysis and research methods for its impact on the sports economy, including the use of Hadoop cloud platform big data processing systems and support vector regression algorithms for cloud platform-based sports big data analysis and sports economy. The experimental results of this paper show that the average correlation between sports big data analysis and sports economic development is 0.5155, and appropriate cloud platform-based sports big data analysis plays a positive role in promoting sports economic development.

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