Integration of Structured and Unstructured Data in the Analysis of E-Commerce Customers

Sulova, Snezhana

doi:10.5593/sgem2018/2.1/s07.063

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…The SOM was proposed by Finnish professor T. Kohonen, a doctor at the University of Helsinki. Prof. Kohonen held that the neurons in a neural network (NN) respond inconsistently to external stimuli, and the entire NN can be automatically divided into different regions based on the responses [9][10][11].…”

Section: Sommentioning

confidence: 99%

A Hierarchical Model of E-Commerce Sellers Based on Data Mining

Bai¹

2020

ISI

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This paper attempts to accurately classify e-commerce sellers based on data mining. Firstly, the original data from an e-commerce platform were preprocessed, and the classification indices were identified from five categories (products, users, traffic, sales and basic attribute). Next, the principal component analysis (PCA) and the self-organizing feature map (SOM) were fused into a hierarchical model that divides e-commerce sellers into three categories: large sellers, medium sellers and small sellers. The effectiveness of our model was verified through experiments. Finally, several operating strategies were put forward for e-commerce sellers in each category. The research results provide a good reference for the development of the e-commerce industry.

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Section: Sommentioning

confidence: 99%

A Hierarchical Model of E-Commerce Sellers Based on Data Mining

Bai¹

2020

ISI

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“…As is known for the processing of non-structured data, there are no established rules, but dierent algorithms are applied, and comparisons are made of the obtained results. dependencies, which in most cases are a source for useful business knowledge [20].…”

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confidence: 99%

An Approach to Storing Data Based on the Data Lake Concept to Facilitate Intelligence Data Analysis

Sulova¹

2020

SJC

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Data analysis is now becoming increasingly more important for business. The accumulation of large amounts of different types of data in organizations is a prerequisite for seeking new ways of storing, processing and analyzing them. The following article presents the nature of the data lake concept and an approach for organizing and storing all the data, both those generated by the software systems in the organizations and those extracted from Internet sources. The approach is based on the combined usage of the concepts data lake and data warehouse and allows the storage of large amounts of data, regardless of its type, structure, or format, and allows for the integrated use of structured and unstructured data and the application of a variety of techniques for intelligent business analysis.

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Integration of Structured and Unstructured Data in the Analysis of E-Commerce Customers

Cited by 2 publications

References 5 publications

A Hierarchical Model of E-Commerce Sellers Based on Data Mining

A Hierarchical Model of E-Commerce Sellers Based on Data Mining

An Approach to Storing Data Based on the Data Lake Concept to Facilitate Intelligence Data Analysis

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