Download Application of Data mining in Electronic Commerce

Application of Data mining in Electronic Commerce
Ling Chuanfan
Jiangxi University of Finance and Economics, P. R. China 330013
Abstract The online portfolio of the e-commerce website is enormous, and it contains a lot of
information of very important user in a large amount of business, but the contradiction between the data
explode and poor information is conspicuous day by day. Through data mining technology, enterprises
can fully utilize various kinds of effective information on Web, mine the potential market, improves the
competitiveness. In this paper, we describe the data mining architecture and the web mining technology.
We further present the e-commerce model based on web mining. We detail the web mining functions
and the data mining process in e-commerce.
Keywords Data Mining, Electronic Commerce, Web Mining
1 Introduction
We are living in a networked era now, and the communication, computer and network technology are
changing the whole human society. ISC (Internet Software Consortium) statistics show that global 233
million host computers have connected with Internet by January of 2004. In our country, the
development of Internet is swift and violent too. According to CNNIC (China Internet Network
Information Center), to June 30, 2004, online computers have attained 36.3 million in our country, and
the number of users 87 million that surf the Internet, and the domains registered under cn are 382216,
and WWW web sites are 626600.
With the development at full speed of Internet and Web technology, all kinds of e-commerce web sites
surge forward, and the development in the whole world of e-commerce is in the ascendant. The trading
value of U.S.A. B2B trade reached 2,700 billion dollars in 2003. According to the estimation by
Forrester Research, the trading value of market of China B2C will reach 27 billion dollars in 2004. The
advantage brought to enterprise, individual and society in development of e-commerce is
omni-directional, and it really brings the mankind into the information-based society.
The e-commerce web site needs to deal with a large number of data every day, but the important
information contained in resources of the data fails to get the abundant mine and use so far. In the fierce
e-commerce market competition day by day, any information related to consumer behaviour is all very
valuable for operator. In order to solve the data explode and information poor phenomenon, data mining
technology arises at the historic moment, and there are extensive application prospects in e-commerce.
2 Data Mining and Web Mining
With the rapid growth of the network information resources, people pay close attention to effectively
take out potential and valuable information from the network information of magnanimity more and
more, and make it function in managing and making policy effectively.
2.1 Data Mining
Data mining is a kind of decision support process, and it is because of such technology as artificial
intelligence, machine study, statistics, etc. mainly, analyses various kinds of existing data increasingly
automated, make summing up reasoning, excavate out the potential mode from it, predict the customer's
behavior, help the policymakers of enterprises to adjust the market tactics, reduce the risk, make correct
decision.
2.1.1 Technology Definition of Data Mining
Look technically, data mining is a process to pick up potential useful information and knowledge from a
large amount of, incomplete, to have noise, a fuzzy one, among the real data at random, draw know by,
people that imply in among them.
2.1.2 Main Technological Reason Exciting Data Mining
Exciting the development of the data mining, the main technological reason used and studied is as
follows: super large-scale database, advanced computer technology, the shortcut of the magnanimity
data, use the profound ability that calculate of statistical method to the data.
2.1.3 Data Mining System Structure
The typical data mining system includes six main parts: Database, data warehouse and other information
storehouse, the database and data warehouse server, knowledge base, the data mining engine, assess the
module in mode, visual user's interface.
Data mining system structure is depicted in figure 1.
Data collection and input
Data mining
engine
Database and data
warehouse server
Database
Data analysis mining
Data warehouse
Mode
assess
Result output
Visual user’s
interface
Knowledge base
Figure 1 Data mining system architecture
2.2 Web Mining
Internet stores a large amount of complicated, no-structuralization, dynamics and incompleteness
information. This information is unable to be handled and managed by using the existing database
management system. The main reason is that the Internet includes a large number of files, figures,
pictures, sound and large-scale commercial data, etc. Users with different backgrounds, different
interests and different purposes have abundant freedom, and they can use these information by random
to connect with any Internet web sites.
Web mining is the extraction of interesting, potential and useful model and implicit information from
artifacts or activity related to the WWW.
2.2.1 Classification of Web Mining
We can classify Web mining into three domains: content, structure and usage mining, as figure 2 shows.
Web mining
Web content mining
Mining based on text
information
Web structure mining
Mining based on
multimedia information
Web usage mining
Generic access
pattern tracking
Individuation usage
record tracking
①Web content mining。It refers the process that we obtain the useful information from the file content
Figure 2 Classification of Web mining
and its description, and it can further divide for mining based on text information and mining base on
multimedia information.
Web structure mining It is a process that we can get useful knowledge from web organization
structure and link relation.
Web usage mining
Analyzing the Web access logs and related data can help understand the browser of the web site and user
behavior model, and it can divide into two domains: generic access model track and individuation use
record track.
2.2.2 Web Mining Technology
Access Analysis. While excavating Web data with this technology, we usually adopt the graphic form,
the page on websites is defined into a node in the picture, and the ultra chain between the pages is
defined into a side in the picture. In process of Web mining, analyzing through access technology can
confirm frequent visit route of website in Web.
②
③
①
。
。
②Association Rules Mining. The purpose is to excavate the interrelation of appearing and hiding
among the data. In Web data mining, the association rules mining should excavate out user's connection
among page (or file) visiting from server during a visit when being excavated, perhaps not have direct
relation of quoting between these pages.
Sequence Model Analysis. Its emphasis point lies in analyzing causality before and after among the
data. In Web server logs, users' visit is recorded by time.
Classification Rules Discovery. It sets up outline characteristic for the specific colony with some
public attribute, and these characteristics can classify newly increased data in database.
Clustering Analysis. It can gather out customer's group with similar characteristic from visited server
information, namely get having users of the similar characteristic, data one together.
③
④
⑤
3 E-commerce Model Based on Web Mining
The online portfolio of the e-commerce website is enormous, and it contains a lot of information of very
important user in every day's a large amount of business. Each customer behavior at Web will produce
relevant data, include message of buying, the relevant data that utilize the search engine and having a look
around in the website again. All mutual data are written down by the backstage supporter's database. Utilizing
perfect database technology, enterprises can collect the information of a large number of customers more
easily. And excavate technology through Web, enterprises can utilize effective customer's information,
explore the potential market, improve the competitiveness.
3.1 Traditional E-commerce Structure Model
In traditional e-commerce structure model (as figure 3 shows), the component related with data mining
has not been introduced. Mobile devices and PC customer client user communicate Web application
server through Internet's protocol and application server and the backstage supporter's database server to
carry on information interchange. It usually works in distributing environment.
Mobile
devices
Application
Server
Data Base
Server
Internet
Client
Figure 3 Traditional e-commerce structure model
The application server offers a running environment for business. In this environment, it is various kinds of
components that every layer application is separated from commercial service, and these components
communicate each other through the network. At present, we have many application servers at choices,
such as IIS server of Microsoft Company, J2EE server of every big company, etc. Run in JVM (Java
Virtual Machine) that the application software uses the server in Web and inlays inside. The components
of these servers utilize the foundation of the network to build up the catalogue offered and security service,
pass HTTP or IIOP (Internet Inter-ORB Protocol) and the customer and other packages communication.
3.2 E-commerce Model Based on Web Mining
The e-commerce model based on web mining include the basic component in the traditional
e-commerce model on the basis of Web, and it has added the knowledge base server, as figure 4 shows.
Mobile
devices
Web application
server
Internet
Client
Data base
server
Data mining
engine
Knowledge base
server
Figure 4 E-commerce model based on web mining
Application server can carry on information interchange with the knowledge base server too except that
exchanges with the database server, after for example use the server to put forward the data to
knowledge base server to excavate asking, the knowledge base server excavates the engine through the
data, excavate and deal with the data to the database, returned and gave and used the server finally.
4 Web Mining Application in E-commerce
The change of the present economic mode, the electronic trade on Internet has changed the relation
between operator and customer. The online customer's mobility is very big. They especially pay
attention to the price of the goods while paying close attention to the goods and meeting their demands.
Enterprises need to know customer's hobbies, value orientations as many as possible, so as to ensure the
competitiveness of times in e-commerce. The potentiality that Web excavates lies in using various kinds
of data to excavate algorithms, analyses such data as the daily record and customer, products and sale on
Internet server, etc.
4.1 Excavating Information from E-commerce
In e-commerce, commercial information comes from various kinds of channels. For example, when
consumers consume with the credit card, operators can collect relevant information in the settlement
course of the credit card, note consumer go on time, place, commodities or services that interested in
that consume, like price competence and solvency, etc. data that receive; When we apply for credit card,
etc. to need to fill in the form, our personal information is stored in the corresponding business database;
Enterprises can also buy necessary information from other companies or the organization besides
collecting relevant business information by oneself . Make up this information from various kinds of
channels, use the treatment technology of information to deal with, receive the decision basis that the
operator is used for carrying on directional marketing to the specific consuming groups or the individual
from it.
For example as operator being through is it after excavating, find to business datum one bank account
holder is it apply double to unite accounts to demand suddenly to go on, and confirm this consumer is
that the first application unites accounts, the operator can infer this user may be going to marry. It can is
it is it buy house, pay children such business of long-term investment as tuition fee, etc. to use for to
promote to this user orientation. The operator may even sell this information and specialize in the
wedding celebration goods and company served. In the countries and regions with more developed
market economy, a lot of e-commerce ventures all begin to excavate and carry on deep processing to
business information through the data on the basis of original information system, in order to construct
one's own competition advantage.
4.2 Web Mining Functions
All visitors of Web website will leave the trace had a look around, and the information is stored in the
logs of Web server automatically. Web analyses tools will become meaningful information next life
through analyzing and dealing with the daily record file of Web server.
Through collecting, processing and dealing with a large amount of information related to consumer's
consumer behavior, we can confirm specific consuming groups or the individual's interest, consumption
habit, propensity to consume and consumption demand, and then infer out the corresponding consuming
groups or individual's next consumer behavior. Then based on this, we can carry on the directional
marketing of the specific content to the consuming groups recognized, save the cost, raise the result,
thus bring more profits to enterprises.
4.2.1 Understand customer's behavior
Know the visitor personal hobby.
Receive the conversion ratio from visitor to buyer.
Find the customer's turning round rate.
Grasp the customer's purchase mode and the visitor mode.
Find common characteristic , customer of group , understand customer group and relation to buy item.
Find the connection between the customer and customer.
Optimizing the management mode of the e-commerce website through understanding the visitor
①
②
③
④
⑤
⑥
dynamic behavior, the website can offer the individualized service to different customers.
4.2.2 Judge the efficiency of Web website
Grasp high purchase rate part and low part of buying, and receive reliable market feedback information.
Know the visit situation of the page.
Find the situation of clicking of the advertisement, assess and test the rate of return on investment of the
advertisement.
Web designer no longer totally depends on determining the nature to guide and design websites of the
expert, but revise and design website's structure and appearance according to the visitor information.
4.3 Data Mining Process in E-commerce
The process of data mining in e-commerce includes three stages: data preparation, excavate operation
and result expression and explanation.
4.3.1 Data Preparation
This stage can divide into such three stature steps as data integrating, data choosing, data pretreatment,
etc. further.
Data integration deals with many files or many database data of running environment to integrate, solve
the fuzzy problem of semanteme. Purposes of data choose are to distinguish data set analyzed to need,
narrow range of processing; improve the quality that the data excavate. The pretreatment of the data is
for overcoming the limitation of the instrument to dig up of data at present.
4.3.2 Data Mining
This stage carries on real excavating and operating, including mainly: determining how to produce
supposing, choosing the suitable tool, exploring the operation of knowledge, verifying the knowledge
found.
4.3.3 Result Expression and Explanation
In this stage, we analyze to the information that is drawn according to the end user's decision purpose,
and distinguish the most valuable information, and refer to a policymaker through the support tool of
decision.
5 Conclusion
Excavating and finding knowledge to the data emerging in the electronic business procedure, it can
contribute to enterprise's making the corresponding sales tactics to different products, and it can
establish the page which meet customer's demand dynamically; It also can contribute to optimizing the
structure of organization of the commercial affair website, and improve the working efficiency of
commercial websites; Contribute to launching goal marketing pointedly. In a word, the data have
excavated and supported such key commercial procedure as CRM, ERP and SCM, etc. effectively in
e-commerce, it is the important means innovated in e-commerce marketing. The application that the data
excavate in e-commerce is a brand-new field, and its development is very fast. A lot of problems await
further research and promotion at the same time.
References
[1] Han J, Kamber M. Data Mining: Concepts and Techniques. San Mateo, CA: Morgan Kaufmann,
2000.
[2] Liu Hongyan, Chen Jian, Chen Guoqing. Review of classification algorithms for data mining, Journal
of Tsinghua University (Science and Technology), 2002,42(6): 727-730[in Chinese]
[3] Mobasher B, Cooley R, Srivastara J. Automatic Personalization Based on Web Usage Mining.
Communications of the ACM, 2000, 43(8), 142-151
[4] Wilvander Aalat, Boudewijn Van Dongen, et al. Workflow mining: A Survey of Issues and
Approaches. Data & Knowledge Engineering, 2003, (47): 237-267
[5] Kanmrani A, Rong W, Gonzalez R. A genetic algorithm methodology for data mining and intelligent
knowledge acquisition, Computer & Industrial Engineering, 2001, 40(2): 361-377
[6] Chakrabarti S. Data mining for hypertext: A tutorial survey. SIGKDD Exploration, 2000, 1(2): 1-11
[7] Srivastava J. et al. Web usage mining: Discovery and application of usage patterns from Web data.
SIGKDD Explorations, 2000, 1(2): 12-23