TITLE:
Data Mining in Electronic Commerce: Benefits and Challenges
AUTHORS:
Mustapha Ismail, Mohammed Mansur Ibrahim, Zayyan Mahmoud Sanusi, Muesser Nat
KEYWORDS:
Data Mining, Big Data, E-Commerce, Cloud Computing
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.8 No.12,
December
28,
2015
ABSTRACT: Huge volume of structured and unstructured
data which is called big data, nowadays, provides opportunities for companies
especially those that use electronic commerce (e-commerce). The data is
collected from customer’s internal processes, vendors, markets and business
environment. This paper presents a data mining (DM) process for e-commerce
including the three common algorithms: association, clustering and prediction.
It also highlights some of the benefits of DM to e-commerce companies in terms
of merchandise planning, sale forecasting, basket analysis, customer
relationship management and market segmentation which can be achieved with the
three data mining algorithms. The main aim of this paper is to review the
application of data mining in e-commerce by focusing on structured and
unstructured data collected thorough various resources and cloud computing
services in order to justify the importance of data mining. Moreover, this
study evaluates certain challenges of data mining like spider identification, data
transformations and making data model comprehensible to business users. Other
challenges which are supporting the slow changing dimensions of data, making
the data transformation and model building accessible to business users are
also evaluated. A clear guide to e-commerce companies sitting on huge volume of
data to easily manipulate the data for business improvement which in return
will place them highly competitive among their competitors is also provided in
this paper.