What is the business value of
AI (Artificial Intelligence)
technologies in business today?
941634 黃竣亨
U.S. Bancorp and Wachovia Bank
──What is the business value of AI technologies in business today?

U.S Bancorp. use a variety of AI tools
called “neural network” to detecting
credit-card frauds. It have slashed such
incidents by 70%.
Wal-Mart
──What is the business value of AI technologies in business today?
Wal-Mart harnesses AI to transform raw
data into useful information and
consolidates point-of-sale details from it’s
3000 stores.
 Wal-Mart uses “data-mining system” to
instantly shift the deluge to uncover
patterns and relationships that would
elude an army of human searches.

Wal-Mart(cont.)
──What is the business value of AI technologies in business today?

The system enable Wal-Mart to predict
sales of every products at each stores
with uncanny accuracy, translating into
huge savings in inventories and maximum
payoff from promotional spending.
Bank Financial
──What is the business value of AI technologies in business today?
Bank Financial Corp. use the Clementine
data-mining “workbench” to develop
model that predict customers’ behaviors
so that bank can accurately target
promotion to customers and prospects.
 Bank Financial Corp. also beginning to use
Product Marketing, a new package of
“best-practice templates” for helping
users set up predictive model .

Bank Financial(cont.)
──What is the business value of AI technologies in business today?

Predictive Marketing will reduce the time
it takes the bank to develop a model. The
first major application is a model to
predict customers churn, the rate at
which customers come and go.
HP
──What is the business value of AI technologies in business today?
HP can use their techniques of “lead
ratings” to predict customer-led ratings
with 85% accuracy.
 HP has an Enterprise Systems Group that
pulls together people with diverse
background and strong analytical skills for
it’s group that does predictive modeling of
customer behavior.

HP(cont.)
──What is the business value of AI technologies in business today?

HP use software to mine its database of
customers and prospects, using AI
techniques to predict customer churn,
loyalty, and where to target marketing.
What are some of the benefits and
limitations of data mining for business
intelligence? Use BankFinancial’s
experience to illustrate your answer.
941633 張耕瑋
What are some of the benefits and limitations of data mining
for business intelligence? Use BankFinancial’s experience to
illustrate your answer.
Benefits :
 understanding and predicting customer
behavior
 cost-saving
 revenue-boosting
 reduce time
 For BankFinancial this means knowing where
to target customer promotions and how to
get new prospects for business growth.

What are some of the benefits and limitations of data mining
for business intelligence? Use BankFinancial’s experience to
illustrate your answer.(cont’d)
Limitations :
Getting daily transaction data
cost of data warehouse
Integrating disparate data sources
 BankFinancial had a lot of difficulty getting
the transaction data in the first place and,
due to different data sources, had trouble
integrating the data into something
meaningful.

What are some of the benefits and limitations of data mining
for business intelligence? Use BankFinancial’s experience to
illustrate your answer.(cont’d)
Why have banks and other financial
institutions been leading users of AI
technologies like neural networks?
What are the benefits and limitations
of this technology?
941633 張耕瑋
Why have banks and other financial institutions
been leading users of AI technologies like neural
networks?

Banks and other financial institutions have
been leaders in using AI, such as neural
networking, because it makes good
business sense. They were able to reduce
credit card fraud and save lots of money
previously lost to these fraudulent
business practices by using neural
networking.
What are the benefits and
limitations of this technology?
Benefits
 increasing income by better
understanding customer desires and
needs
 less formal statistical training
 Limitations
 Integrating disparate data sources
 Getting daily transaction data
 The data mining project is only as good
as the data available to sift through.

Benefits to other industries

Marking/Retailing
◦ Aid direct marketers by providing them with useful and accurate
trends about their customers’ purchasing behavior. Based on
these trends, marketers can direct their marketing attentions to
their customers with more precision.

Banking/Crediting
◦ Data mining can assist financial institutions in areas such as
credit reporting and loan information.

Law enforcement
◦ Data mining can aid law enforcers in identifying criminal suspects
as well as apprehending these criminals by examining trends in
location, crime type, habit, and other patterns of behaviors.
Limitations
Security issues
 Although companies have a lot of personal
information about us available online, they do
not have sufficient security systems in place to
protect that information.
 Misuse of information/inaccurate
information
 Trends obtain through data mining intended to
be used for marketing purpose or for some
other ethical purposes, may be misused.

Describe what the AI in the
real case is all about?
941621 江秉憲
Artificial Intelligence(AI)
Artificial intelligence is the intelligence of
machines and the branch of computer science
which aims to create it.
2. The field was founded on the claim that a
central property of human beings, intelligence
can be so precisely described that it can be
simulated by a machine.
3. Artificial intelligence, by claiming to be able to
recreate the capabilities of the human mind.
1.
What is an Expert system？
- Techniques of AI
An expert system is software that attempts to
reproduce the performance of one or more
human experts.
2. A traditional application of artificial intelligence.
3. Once the system is developed, it is proven by
being placed in the same real world problem
solving situation.
1.
What is an Expert system？(cont.)
- Techniques of AI

Two main methods of reasoning :
1. Forward chaining - An inference engine
using forward chaining searches the
inference rules until it finds one in which the
if clause is known to be true. It then
concludes the then clause and adds this
information to its data.
What is an Expert system？(cont.)
- Techniques of AI
2. Backward chaining - An inference engine
using backward chaining would search the
inference rules until it finds one which has a
then clause that matches a desired goal. If the
if clause of that inference rule is not known
to be true, then it is added to the list of
goals. EX:
 If Fritz is green then Fritz is a frog.
 If Fritz is a frog then Fritz hops.
What is an Neural networks?
- Techniques of AI
1.
An artificial neural network (ANN), also
called
1. a simulated neural network (SNN)
2. neural network (NN)
What a neural network is, most would agree
that it involves a network of simple processing
elements (neurons) determined by the
connections between the processing elements
and element parameters.
3. In a neural network model, simple nodes are
connected together to form a network of
nodes —"neural network."
2.
What is an Neural networks?(cont.)
- Techniques of AI
4.
In most cases an ANN is an adaptive system
that changes its structure based on external or
internal information that flows through the
network.
• An adaptive system - is a set of interacting or
interdependent entities, real or abstract, forming
an integrated whole that together are able to
respond to environmental changes or changes in
the interacting parts.
What is Data-mining?
- Techniques of AI
Data-mining is the process of extracting
hidden patterns from data, as more data is
gathered, data mining is becoming an
increasingly important tool to transform this
data into information.
2. The term data-mining is often used to apply to
the two separate processes of knowledge
discovery and prediction.
1.
1. Knowledge discovery - provides explicit
information about the characteristics of the
collected data.
2. Forecasting and predictive modeling - provide
predictions of future events.
What is Data-mining?(cont.)
- Techniques of AI

Data mining commonly involves four classes
of task :
1. Classification - Arranges the data into predefined
groups.
2. Clustering - Is like classification but the groups are
not predefined, so the algorithm will try to group
similar items together.
3. Regression - Attempts to find a function which
models the data with the least error.
4. Association rule learning - Searches for
relationships between variables.
What are the advantage
and disadvantage of the AI?
941627 張書銘
Advantages
Wal-Mart
1.Transform raw data into useful data in
high efficiency.
2.Help them predict sales with uncanny
accuracy.
3.Huge savings in inventories.
4.Maximum payoff from promotional
spending.

Advantages (cont.)
BankFinancial
1.Accuracy number calculating.

2.Faster math model developing.
3.Predict customer behavior.
4.Help them make promotion plans.
Advantages (cont.)
HP
1.Predict customer behavior.

2.Help them make the promotion plan.
3.Analysis personnel’s assessments with
complex data.
Disadvantages

Data transaction issues
A huge amount of data need transform into regular files.
Make them can be read by AI analysis process.

Data collection issues
There are some difficulties with raw data collection.
These data sources are disparate could be from
database, writing records, phone calls, etc.
Disadvantages (cont.)

Timeliness issues
Decision maker and his group member can get a result
directly and quickly. They don’t need transform data to a
specification format. Because of that, AI may be useful in
strategy decision making rather than tactics.

Limited functionality
Every AI had a specialty in solving problems, but they
can’t solve other issues which they are not designed for.
Disadvantages (cont.)

No creative, less adaptability
AI provides good solutions but may not the best. Some
small signs or unpredictable events can’t input into AI,
like people emotion, natural disaster, etc.
These things are hard to quantify, only people can deal
with them.
How does the AI change the
way new business operate
now?
941651 林虛白
Stocks-Wal Mart
Without AI
Company will replenish when
stocks less than safety stock.
With AI
Company analyzes goods by data
mining.
The safety stock will be changed
with the report.
Marketing strategy-WWE
Without AI
With AI
Sales staff uses historical case to
develop the Marketing strategy.
But Sales staff can not accurately
develop strategy for all customer.
Company analyzes the older data
by data mining , and finds the most
important goods for customer.
Company uses the reports to
enforce One to One Marketing.
Credit card issuing-HSBC
Without AI
User views customer’s
information to determine
whether credit cards be issued .
With AI
Use the Neural Network to
analyze the customer's financial
information and credit rating and
determine the credit Rating of the
credit card holders.
The place of goods-Wal Mart
Without AI
According to the price and the
category of the commodity , the
company decided the place of the
commodity .
With AI
The company analyzes past
information to find the
relationship between goods and
goods by data mining and
determines the place of goods.
Choose types of ground-CAD System
Without AI
Architects judge what type
ground is better by construction
conditions and geological data
by experience . But architects
can not accurately judge the right
type of ground.
With AI
Architects use neural network
to analyze construction
conditions and geological data
and know what type of grounds
is better chosen.
Determine Cancer
–Kaohsiung medical university Chung-ho
memorial hospital
Without AI
Based on palpation and the
report ,doctors can know
whether patient has malignant
tumor.
With AI
Doctor use neural network to
analyze samplings.
Based on the results of the analysis
doctors can accurately determine
whether patient has malignant
tumors.
Forecast Stock index
–Beat Wüthrich Vincent Cho
Without AI
With AI
Analysts analyze the K-line 、
BIAS 、 WMS 、KD value and
historical Stock index to forecast
the future value.
Analysts use the neural network
to analysis historical stock index.
Analysts can know the correlation
between each stocks.
Analysts can use the report to
forecast the change of the stock
index.
Players’ career Analysis
-Baseball Analysts
Without AI
Analysts use statistical methods
to analyze players’ data and
forecast the future performance
of the players.
With AI
Analysts use neural network to
analyze players’ data. Analysts can
more accurately forecast the
future performance of the players.
Experimental design - ACS
Without AI
Experimenters find the best
experimental condition and
the methods of design product
by try and error.
With AI
ACS uses neural network and
Fuzzy Theory to build a
system.
This system can find the best
model of experimental design
and reduce the time of try and
error.
Besides those mentioned in
the case, what other ways
can a business realize more
business benefits from the
AI technique?
941641 李昌諭
Market Basket Analysis
941641 李昌諭
Market Basket Analysis
Rule
AD
CA
AC
B&CD
Support
Confidence
2/5
2/5
2/5
1/5
2/3
2/4
2/3
1/3
941641 李昌諭
Market Basket Analysis

Advantages
1. Computing model is easy-to-read
2. Conclusions are easy-to-read
3. Can analyze the different forms of raw data

Defects
1. When goods increase in the number of operations
will be followed by an increase geometrically
2. Special attention not to the individual
characteristics of goods
3. Difficult to determine the appropriate combination
of a few commodities
941641 李昌諭
4. Easy to remove a rare commodity
Wal-Mart
Knows the appropriate combination of
commodities at different positions and in
different time.
 Drive propositions, advert and product
placement.
 Babies nappies (diapers) and beers purchases
revealed that they
were made by men, on Friday
evenings mainly
between 6pm and 7pm.

HP


The components of the computer suite
and the peripherals.
Most students will purchase computers
with good graphics card, speaker, LCD, and
joy sticks during summer vacation.
941641 李昌諭
HP

The consumer will buy printer, and they
also may buy ink, toner, or paper.
941641 李昌諭
Credit Rating




Estimates the credit worthiness of an
individual, corporation, or even a
country.
An evaluation made by credit bureaus of
a borrower’s overall credit history.
Calculated from financial history and
current assets and liabilities.
Tells a lender or investor the probability
of the subject being able to pay back a
loan.
941641 李昌諭
The factors which may influence a
person's credit rating






Ability to pay a loan
Interest
Amount of credit used
Saving patterns
Spending patterns
Debt
941641 李昌諭
BankFinancial


Used to adjust insurance premiums,
determine employment eligibility, and
establish the amount of a utility or
leasing deposit.
A poor credit rating indicates a high risk
of defaulting on a loan, and thus leads to
high interest rates, or the refusal of a
loan by the creditor.
941641 李昌諭
Do some searches from the web
and provide some historical
background about the mentioned AI
(Artificial Intelligence)?
941636 楊銘鴻
Historical background of AI
1950, Alan Turing took a experiment to
test a question : “ Can machines think?”
 The machines pass the experiment If 30%
users had been cheated.

A
B
Is A the
human or is B?
941636 楊銘鴻
Historical background of AI (cont’d)

What theories were AI based on ?
- Philosophy
- Mathematics
- Economics
- Psychology
- Linguistics
Logic, methods of reasoning.
Proof algorithms,computation, probability.
Utility, decision theory.
Using the tools and methodologies to
observe human thought.
Knowledge representation, grammar.
941636 楊銘鴻
Historical background of AI (cont’d)

1956-1970:
1956, John McCarthy coins the term, "Artificial
Intelligence" at a Dartmouth computer
conference.
 1958, John McCarthy invents the Lisp language,
an AI programming language, at Massachusetts
Institute of Technology (MIT).
 At that time computer abilities were limited , a
program that can perform something intelligent
is shocking.

941636 楊銘鴻
Historical background of AI (cont’d)

1970-1979 :
1972: Alain Colmerauer writes Prolog.
 1974: Ted Shortliffe creates MYCIN, the first
expert system which showed the effectiveness
of rule-based knowledge representation for
medical diagnosis.


Although expert system grow fast but AI
develop slowly in this period .
941636 楊銘鴻
Historical background of AI (cont’d)

1980 - present :
Application of AI :
- Autonomous Planning and Scheduling.
- Autonomous Control.
- Data mining.
- Robotics.
 1995 :The emergence of intelligent agents.

941636 楊銘鴻
Historical background of AI (cont’d)
1997: IBM computer Deep Blue using AI
technology beats world champion Garry
Kasparov in chess match.
 It means a big milestone.
 That success is ascribe on
strong computation ability
and enough storage.

941636 楊銘鴻
Describe who else may find
the AI useful. Give at least 5
examples. And, why do you
think so?
941624 劉柏宏
Surveillance
─U.S. government

Previous data mining to stop terrorist programs under the U.S.
government include：
◦ Total Information Awareness (TIA) program
◦ Computer-Assisted Passenger Prescreening System (CAPPS II)
◦ Analysis, Dissemination,Visualization, Insight, Semantic Enhancement
(ADVISE)
◦ Multistate Anti-Terrorism Information Exchange (MATRIX)
◦ Secure Flight program

Today many records are electronic, resulting in an "electronic
trail".
◦ When many such transactions are aggregated they can be used to
assemble a detailed profile revealing the actions, habits, beliefs, locations
frequented, social connections, and preferences of the individual.
◦ This profile is then used, by programs such as ADVISE and TALON(Threat
and Local Observation Notice) , to determine whether the person is a
military, criminal, or political threat.
Surveillance(cont.)
─U.S. government

These programs have been discontinued
due to controversy over whether they
violate the US Constitution's 4th
amendment.
Center for Disease Control
─Applying Text Mining to Assist People Who Inquires
HIV/AIDS Information from Internet


The present research proposes an Internet health
information governance mechanism (IHIGM) for support
the diseases control and health authority to do their
efforts in Internet health information.
In the experiment, the research takes “People Inquire
HIV/AIDS Information
from Internet” as example
and explains the procedure
of IHIGM.
Center for Disease
Control(cont.)
─Applying Text Mining to Assist
People Who Inquires
HIV/AIDS Information from Internet

Part A
◦ is health information from Internet by Questioners or Repliers.
◦ There is a web crawler to gather related HIV/AIDS health information by
Questioners or Repliers from Internet then into part B.

Part B
◦ The HIV/AIDS health information document will be recorded in stage I, such as
Questioner/ Replier ID, title, content, link and time.
◦ The title and content of each document will be extracted by word segment
technique to find valuable terms to represent the document in stage II.
◦ Then in stage III, there is a baseline matching skill for four scenarios which provided
by domain expert and mentioned above to classify the target health information to
intervene.

Part C
◦ The authority can make responding strategies for the target health information to
show efforts for health information in Internet.
Hospital
─St. Joseph Mercy Hospital

Diagnose Heart Attacks
◦ traditional
 electrocardiogram (EKG)
 Exam
 blood analysis
◦ A physician at St. Joseph Mercy Hospital in Michigan
designed a neural network that recognizes cases of acute myocardial
infarction (AMI, commonly called heart attack) using the cardiac
enzyme data from series of tests on patients.
◦ The input consisted of two sequential cardiac enzyme tests and the
number of hours between the tests. The output was "1" if the
patient had a heart attack and "0" if the patient did not. The
network was trained with 185 examples from 47 patients using
blood tests that were not more than 48 hours apart.
◦ The network agreed with 100% of the AMI cases diagnosed by the
cardiac enzyme expert, and 93% of the non-AMI cases. The 7%
difference occurred where the network was uncertain.
Telecommunications
─MCI Communications
 MCI would like to remain the most customers. One way is
to find the customers timely who consider changing the
company. Then MCI can try to remain them, such as
providing special rates and services.
◦ But how do you find the customers who you need to remain？
 MCI searches the information of the 140 million families.
Attributes of each family are up to 10,000. These include
income, lifestyle, customary to call, etc.
 To identify the model, MCI use its data warehouse to find
the most significant variables, and pay close attention to
these variables.
Supermarkets
─Safeway

Issue credit cards for customers
◦ The Consuming Behaviors of these customers have been
stored
◦ A week stored about 500GB in the Data Warehouse
◦ then they use Association (such as Market Basket
Analysis) compared to the collection which includes
transaction data and product data, and then set a list
of attractive products.
 customers who buy barbecue charcoal, in 75% will purchase
lighter fuel
 a cheese product ranked 209 in sales, but The highest spending
customers in 25% are often bought this cheese
 28 brands of orange juice, There are eight particular favorite
brands. Therefore the company rearranges the display cabinets,
making the amount of sales can be maximized