A Novel Technique for Behavioral Analytics Using Ensemble Learning Algorithms in E-Commerce

doi:10.1109/ACCESS.2020.3016419

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A Novel Technique for Behavioral Analytics Using Ensemble Learning Algorithms in E-Commerce

2020-01-01

Mohammed Alojail

Surbhi Bhatia *

DOI：10.1109/ACCESS.2020.3016419

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Abstract

En 中文

The era of E-commerce and availability of data in every field of operations in an enormous volume that implies to Big Data is one of the biggest sources of competitive advantage for the organizations in this digital world. It provides useful information to grow businesses by posting the advertisement and help consumers find the relevant product according to their preferences. The focus of this research is on the advertisement strategies analysis under which a Business employs several online advertisement strategies in order to appeal to the consumer. This research work will present a detailed analysis in user behavioral to use for business or Online Behavioral advertising and provide the framework of how Enterprise Resource Planning systems track the targeted audience and show their content. The paper's prime objective is to classify and effectively run targeted advertising using the data that shows user's retail behavior. This is where an Enterprise Resource Planning driven data will give rise to behavioral analytics. In addition to this, various data streaming technologies are also emphasized that will help to create a pipeline for the huge amount of data in Enterprise Resource Planning's database.

Keywords:

Databases

Advertising

Classification algorithms

Analytical models

Clustering algorithms

Organizations

Behavioral analytics

ERP

CRM

OBA

business

ensemble learning

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