Research on E-Commerce Promotion System Based on Web Data Mining Technology

Guang Biao Deng

doi:10.4028/www.scientific.net/AMM.686.311

Paper Titles

Research on Employment Data Mining for Higher Vocational Graduates
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Mapping Research Fronts of Big Data Study in 21^st Century
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Design and Implementation of Office Management System in Small and Medium Sized Enterprises Based on Data Mining Technology
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Research on the Distributed Data Mining Cloud Framework Oriented Internet of Things
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Research on E-Commerce Promotion System Based on Web Data Mining Technology
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Design and Implementation of Embedded Database Based on File System – The Design and Implementation of EDB
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Study on the Data-Mining Based Mechanism for the Occurrence of Ship Collision Accidents Caused by Human Factors
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The Application of High-Density Resistivity Method to the Evaluation on the Stability of Gongchangling Open Pit's Slope
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The Application of Fuzzy Equivalence Relation Based on the Quotient Space in Cluster Analysis
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 686Research on E-Commerce Promotion System Based on...

Research on E-Commerce Promotion System Based on Web Data Mining Technology

Abstract:

This paper describes the use of Web data mining, and analyze the data on the web site (including the server log, commercial database, user database, the shopping cart, user mode) that access to relevant knowledge for goods, commodities such as preference relations. Secondly, the static model of the data mining methods, it is a manifestation of the site management personnel marketing thought. Based on these models, the paper proposed strategy for the site registered users, and produces the corresponding calculating formulas of a good recommendation and the corresponding recommendation algorithm for the current user, thus to get a user recommendation.

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Periodical:

Applied Mechanics and Materials (Volume 686)

Pages:

311-315

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.686.311

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Online since:

October 2014

Authors:

Guang Biao Deng

Keywords:

Data Mining, E-Commerce, Recommended Values, Web Data Mining

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