science · clementine 12.0 statistica 7.0 weka r cloud r r+excel add-in …….more and more -48-...
TRANSCRIPT
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Ben-Chang Shia Professor of department of statistics and information Science & Applied Statistics
Chairman of Graduate School of Business Administration, Fu Jen Catholic University. Chairman of ChungHwa Data Mining Association
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WWW.CDMS.ORG.TW
18, OCT.,2012
Statistics Trend--Trend Statistics
11 FEBRUARY 2011 VOL 331 SCIENCE www.sciencemag.org
Science Dealing with DATA
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Cloud Computing The large arithmetic processing
program through the network will automatically split into numerous smaller subroutine, and then by multiple servers consisting of large systems. After searching, processing and then return the results to user.
Cloud Computing～=Network Google：MapReduce、GFS and
BigTable 7
Grid
Computing
Utility
Computing
Cloud
Computing
Cluster
Computing
Distributed
Computing
Super
Computer
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IaaS
Infrastructure as a Service
PaaS Platform as a Service
SaaS Software as a Service
IIaaS I2aaS Information & intelligence as a Service
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PC Architecture
DOS Spreadsheets
Word Processors
PC Mid 80s
Internet Mid 90s
Applications Late 80s-Mid 90s
Web Apps Mid 00s - . . .
Today
Speech/Writing
XML/SOAP
HTTP/HTML
SMTP Email Clients
Web Browsers
Wi-Fi/Broadband Devices
Web Services
Rights Management
Trusted Computing Hardware
Mouse
GUI
LANs
Cloud Computing
「Computer vs. human brain 」puzzle game, after three days of contest, IBM supercomputer-Watson beat humans eventually, and it was awarded $ 1 million prize. IBM will donate the prize money to charities such as World Vision.
(Data from Associated Press)
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Researchers of IBM spent four years to build Watson, 80 trillion operations per second capacity. When Watson be asked questions, the software will begin analysis the name, data, location, or other conditions to solve the problrm.
IBM don’t plan to participate in the next contest, or create the second generation of Watson. But they plan to promote and apply the technology in different field such as health care.
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Introduction to
Cloud Computing
Cloud Computing: spliting huge computing into hundreds of smaller operations, and then operating simultaneously. Because of Cloud Computing, information which users need can be provided within seconds.
Google search service, Gmail, YouTube, Google
Docs, Google Talk, iGoogle, Google Calendar utilization of Cloud Computing. And Others, such as Microsoft, YAHOO, AMAZON also using this technology to enhance the services of network.
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Google search
Web Email
Online Virus Scanner
YouTube
Online file
Blog
…
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Super
Computer
Roadrunner is set by IBM which was established for
the Department of Energy belongs to the National
Nuclear Security Administration, NNSA .
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Cluster computing Connected through a
group of loosely integrated calculator and hardware to complete the calculation
PVM、MPI
1960~
Relative to supercomputers has higher value.
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Cluster
Computing
Super
Computer
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Distributed Computing Divided computing engineering
data into small pieces, were
calculated by the compute, and
uploaded derived data after the
result of the operation.
find new drugs
E-MAIL : [email protected]
Cluster
Computing
Distributed
Computing
Super
Computer
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Grid Computing A large number of heterogeneous
compute (usually for the desktop) unused resources (CPU cycles and disk storage) as a virtual calculator cluster embedded in a distributed telecommunications infrastructure to solve large-scale computational problems providesa model.
Globus
1990~
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Grid
Computing
Cluster
Computing
Distributed
Computing
Super
Computer
Utility computing Advocating an ideal about
enterprise’s information architecture to let IT services to imitate the way of public services, such as water supply, electricity, gas. "How much you use and how much you pay " and "demand-use"
From IBM,
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Grid
Computing
Utility
Computing
Cluster
Computing
Distributed
Computing
Super
Computer
Cloud Computing The large arithmetic processing
program through the network will automatically split into numerous smaller subroutine, and then by multiple servers consisting of large systems. After searching, processing and then return the results to user.
Cloud Computing～=Network Google：MapReduce、GFS and
BigTable 27
Grid
Computing
Utility
Computing
Cloud
Computing
Cluster
Computing
Distributed
Computing
Super
Computer
The main content of four major
programs The first program of 12th Five-
Year Period is Business Register, the second is Integrated questionnaire for enterprises, third is data collection and processing software, and the final program is online reporting system. That are the main content of four major programs .
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This is the concept of cloud computing –
fast computing & mass storage
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1.台湾PC硬件的第二春? 2.小虾米V.S.大鲸鱼? 3.软硬通吃? 4.众志成城? Data Center虚拟现实
1/17/2007 32
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Nortel Steel Enclosure Containerized telecom equipment
Sun Project Black Box 242 systems in 20’
Rackable Systems 1,152 Systems in 40’
Rackable Systems Container Cooling Model
Caterpillar Portable Power
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1/17/2007 35 1/17/2007 36
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1/17/2007 37 38
Large-scale Virtualization
High reliability High versatility
High scalability
Be paid by User
Low cost
Windows
Amazon
Yahoo
…
39 40
IaaS
Infrastructure as a Service
PaaS Platform as a Service
SaaS Software as a Service
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service
Property
Amazon
EC2
App Engine
Microsoft
Azure
Yahoo
Hadoop
Framework Iaas/Paas Paas Paas Software
Service
Types
Compute/
Storage
Web application Web and non-
web
Software
Management
techniques
OS on Xen
hypervisor
Application
container
OS through
Fabric
controller
Map / Reduce
Architecture
User
Interface
EC2 Command-
line tools
Web-based
Administration
console
Windows Azure
portal
Command line
and web
APIs yes yes yes yes
Fee yes maybe yes no
Programming
Language
AMI(Amazon
Machine Image)
Python .NET
framework
Java,
Database systems,
Data Warehouses,
OLAP
Machine learning
Visualization
Mathematical
programming
High
performance
computing
Data Mining
Statistical and data
analysis methods
Business
Understanding
Data Preparation
Evaluation
Data
Understanding
Modeling
Deployment Data
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Decision Tree Cluster Time Series
Sequence Clustering Association Rules
Naïve Bayes
Artificial Neural
Network
SQL Server 2000 has been provided
Logistic Regression
Linear Regression Text Mining
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•Binary Classifier (二元分类)
•Numeric Predictor (数值预测)
•Time Series (时间序列)
•C&R TREE (分类回归树)
•Quick Unbiased Efficient Statistical Tree (QUEST判定树模型)
•CHAID (分类树)
•Decision List (判定树列表)
•Regression (线性回归分析)
•PCA/Factor (主成分分析)
•Neural Net (类神经网络)
•C5.0 (判定树)
•Feature Selection (特征选取)
•Discriminant Analysis (判别分析)
•Logistic (罗吉斯回归)
•Generalize Linear Model (广义线性模型)
•Cox Regression
•Support Vector Machine (SVM支持向量机)
•Bayes Net (贝氏分类器)
•SLRM (自我学习反应模型)
•GRI关联
•Apriori关联
•CARMA关联(连续交易)
•Sequence Clusterc序列关联
•K-Means (K-Means分群)
•Kohonen (自我组织化)
•Two-Step (二阶段)
•Anomaly (异常检测)
•Random Forests (随机森林)
•ICA (独立成分分析)
•Multivariate adaptive regression spline (MARS多元适应性回归平滑)
•Pmml(预测模型标记语言)
•Boosting
SQL server 2008
SPSS 17 (PAWS) --IBM
SAS
SQL 2008+Excel (2008)-Data Mining
Add-in
Clementine 12.0
Statistica 7.0
WEKA
R Cloud R
R+Excel ADD-IN …….more and more
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RExcel ◦ The Founding of RExcel
◦ Start RExcel
◦Application of RExcel Import Data
Data Analysis
Save Output
2013-3-10 -
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Thomas Baier（1971-）
Application of R in different environments
R/Scilab (D)COM Server- RExcel (1998)
Erich Neuwirth（1948-）
The main author of RExcel
•http://rcom.univie.ac.at/
RExcel founding
University of Vienna
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Install ◦ Manual Install step-by-step by the Manual
◦ Download RAndFriends.rar
Installation Notes ◦ Ｒ-Version 2.9.0 or above
◦ Excel- Version 2003 or Version 2007
RExcel之启动 -
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Any program can be written in the cell, Commander and R console
The right figure demonstrated the right function.
Three parts of
RCommander
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Statistics ◦ Descriptive statistics, simple parametric and non-
parametric tests, linear model
Graphs ◦ All kinds of Statistical charts
Statistical model Distributions ◦ Various quantile, sampling, tail probability
2013-3-10
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Can be stored in Excel
The right figure demonstrated other storage methods.
2013-3-10
Banking and Financial Service ◦ Customer contribution, Credit score, Risk assessment,
Customer segmentation, Cross-marketing, etc
Insurance ◦ Customer contribution Credit score, Risk assessment,
Customer segmentation, Cross-marketing Customer churn analysis and fraud detection, etc
Telecommunications industry ◦ Customer contribution Credit score, Risk assessment,
Customer segmentation, Cross-marketing Customer churn analysis, Sales Forecast and fraud detection, etc
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Manufacturing ◦ Customer contribution analysis, quality management,
marketing, performance analysis, production analysis and inventory analysis, etc.
Retail Business ◦ Customer loyalty, customer segmentation, market basket
analysis, pricing analysis, cross-marketing and sales forecasts, etc.
• Biotechnology, healthcare, aviation industry, environment , legal, and etc
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Applications of Data mining in Different Industries
How to collect data ◦ Operating data, market research data and Panel Tracking
How to manage data ◦ ETL，Data warehousing
How to get intelligence from data ◦ Data Mining，OLAP，Statistics
How to use intelligence ◦ Marketing strategy, Decision-making, Interactive CRM
mechanism
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Using data warehousing to modeling or data extraction by cloud computing.
And pay to using data mining tools and business intelligence online.
The principle of data mining is similar to
business intelligence, both of them are provide information to produce knowledge by data and then accumulation of knowledge.
Cloud computing make this process can be achieved on the Internet.
We can say: cloud computing can provide services (Information & Intelligence as a Service) which based on the SaaS and analysis. It referred IIaaS (I2aaS) and it is an extension of SaaS.
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IaaS Infrastructure as a Service
PaaS Platform as a Service
SaaS Software as a Service
IIaaS I2aaS Information & intelligence as a Service
PC Architecture
DOS Spreadsheets
Word Processors
PC Mid 80s
Internet Mid 90s
Applications Late 80s-Mid 90s
Web Apps Mid 00s - . . .
Today
Speech/Writing
XML/SOAP
HTTP/HTML
SMTP Email Clients
Web Browsers
Wi-Fi/Broadband Devices
Web Services
Rights Management
Trusted Computing Hardware
Mouse
GUI
LANs
Cloud Computing
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On the one hand, can be realized efficient computation of data warehouse through the cloud computing.
And on the other hand, can use tools of data mining and business intelligence analysis software online.
Data from:http://www.guidertech.com/02_produter_15.htm Data from:http://www.guidertech.com/02_produter_15.htm
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Affective computing is responsible for the relevant information with
human affection, focusing on the recognition and expression of
affection. Judging user’s feelings to understand the impact of their
behavior.
The affection is external feelings, that is easy observed and found.
Using photographic equipment and computer to recognize user's
emotions, such as joy, anger, sadness, happiness. Affection is easy
observation and expression of a non-verbal way.
Brotherhood
calculation
Content Recognition accuracy
Speech
recognition
Based on sound electrical diagram ups and downs or the
tone of voice. Usually also with detection analysis of
physiological signals to improve the recognition rate.
50% to 87.5%
Read body
language
According to the movement and posture of user's head,
hands and feet to determine their intentions and affective.
Lower than the facial
recognition and detection
analysis of physiological
signals
facial
recognition
The face is divided into several feature region, such as
eyebrows, eyes, mouth, etc.
Observation and analysis of its expression changes.
The facial expression is the most direct expression of
affection, it's the highest recognition rate.
88% to 89%
detection
analysis of
physiological
signals
Detect user physiological signals, such as heart rate, body
temperature, actin current graph, blood pressure, skin
conductivity, respiration rate, and so on, using the
medical analysis to identify possible affection.
81%
Cloud health care platform is a cloud-based services platform (Figure 15), which includes three main modules: data administrator, cloud health administrator and interface administrator.
The data administrator will collect the old person’s physiological signals and image data at home, then through the feature extraction and data fusion technology to take important health information.
The data administrator will collect the elderly home physiological signals and image data, through the feature extraction and data fusion technology to remove important health information.
Cloud health care administrator will responsible for the situational analysis, behavior recognition, sleep and affective.
Interface administrator responsible for user authorization, cloud sharing, emergency medical and pervasive services.
Name Function Application
Administrator of
Data
Data collection RFID technology, unlimited sensing
network,
Accelerometer
Feature Extraction Signal analysis, image processing
Data fusion Intelligent systems
Administrator of
Cloud health care
Scenario Analysis Situational model, ontology
Behavior Identification ANN
Sleep analysis Machine learning and reasoning
methods
Affective analysis Fuzzy Theory
Administrator of
Interface
User Authorize User model, authorization,
authentication mechanisms
Cloud sharing Cloud gateway, HL7 Agreement
Emergency medical Intelligent agents
Service Common interface of mobile devices,
services Search
On the one hand, can be realized efficient computation of data warehouse through the cloud computing.
And on the other hand, can use tools of data mining and business intelligence analysis software online.
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Strengthening the application of surface, and take advantage of
the advanced features of data mining to match the business
needs, for example, the cross-marketing and BASELII
DATA MINING enhanced performance and features to attract our
upgrade.“Quanta combined Intel with SQLServer, the cost is
lower than the cost of one-third of the Unix, the Quanta create
absolute cost advantage "
DATA MINING improve performance significantly. The original Unix database perform a data processing about 5 minutes, but in SQL Server2008 UDM model, 32 bit just need 23 seconds, and 64 bit just
11 seconds..Each report average development time about one week before, but now, you only need half a day in the new environment.
DATA MINING have more tools and functionality, and both the
leading brand with BI, but the investment costs are much lower.
that meets the goals of ICP Electronics to achieve maximum
benefits with minimal investment.
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Information Telecom Statistics
Social Network Analysis
Empirical Rules
Criminology
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20
77
78
79
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Keyword &
Browsing behavior
statistics Knowledge
Community
Data Mining
Center
Re
co
mm
en
de
d
National Library
Window on
Taiwan
2004.1
National Center
for Traditional
Arts
Archive System
2004.11
Ministry of
Foreign Affairs
Digital Imaging
Database
2004.12
2002 2006
Museum of
Taiwanese
Literature
Literary relics
Digital
Repository
System
2006.5
National Palace
Museum
Digital map file
data management
system
2006.5
Taiwan Normal
University
Roots Network
2002.3
Archives and
Records
Administration
Files Knowledge
Base2003.9
National
Center for
Traditional
Arts
Thematic
knowledge
network
2006.12
National Library
Taiwan Memory
2002.12
Council for
Cultural
Affairs
National culture
Database
2003.1
Council for
Cultural Affairs
Books and Video
Publication
system
2005.3
Council of
Indigenous Peoples
Taiwanese
aborigines
Audio-visual
database
2005.5
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Customer-focused Operations-focused Research-focused
●Life-time Value
●Market-Basket Analysis
●Profiling &
Segmentation
●Retention
●Target Market
●Acquisition
●Knowledge Portal
●Cross-Selling
●Campaign Management
●E-Commerce
●Profitability Analysis
●Pricing
●Fraud Detection
●Risk Assessment
●Portfolio Management
●Employee Turnover
●Cash Management
●Production Efficiency
●Network Performance
●Manufacturing
Processes
●Combinatorial
Chemistry
●Genetic Research
●Epidemiology
Define the problem
Data collection and select
Data processing
Data Parsing
Variable screening
sampling
Data classification
Build a model
Model evaluation and validation
The optimal model
Implement
Basic data
Financial Information
Reporting format
1噪声处理
2Impute missing values
Tax evasion: non-tax evasion
1：1
1：2
1：3
Variable conversion
Descriptive statistics
Correlation
Correlation coefficient
Chi-square test
Training data: Testing data
70%：30%
Accuracy rate
Recall
Precision
F-measure
AUC
Gini coefficient
Decision Tree
Neural network
Logistic regression
Support Vector Machine
Random Forests
Data Compilation
SPSS19
AppServ
R
Intelligent Tax Model
Building
System
Statistical Analysis
AppServ
MySQL
PHP
Apache
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Design
Service
Modeling
Approach Neural
Network
Decision
Tree
Logistic
Regression
SVM
Random
Forests
http://140.136.134.52/ias
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
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• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Upload page • Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Check the data you upload
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
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Select analysis modeling • Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Select For independent variables and dependent variables • Data
preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Select the ratio of test sample to the total sample • Data
preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Results • Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
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Model assessment • Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
The model of Logistic regression
• Data preparation
• Introduction of
Intelligent Tax
Model
• Sampling ratio and Model comparison
• Modeling
• Assessment and
Verification
Sampling
ratio
Modeling
approach Assessment Mean Minimum Maximum
Standard
deviation
1:3
Random Forests
Accuracy 96.89% 95.64% 97.74% 0.000022
Recall 94.81% 92.86% 96.79% 0.00005
Precision 92.53% 88.96% 94.37% 0.000158
F-measure 93.65% 91.45% 95.49% 0.000085
SVM
Accuracy 85.34% 84.40% 86.06% 0.000018
Recall 79.72% 77.07% 82.16% 0.000133
Precision 55.82% 51.47% 60.17% 0.000397
F-measure 65.62% 61.72% 68.00% 0.00023
ANN
Accuracy 74.82% 73.65% 76.21% 0.000028
Recall 0.18% 0.00% 0.64% 0.000003
Precision 32.67% 0.00% 100.00% 0.09652
F-measure 0.35% 0.00% 1.28% 0.000012
Decision Tree
Accuracy 85.71% 84.21% 86.28% 0.000022
Recall 72.80% 68.90% 74.20% 0.000148
Precision 68.31% 65.33% 70.20% 0.000112
F-measure 70.47% 67.07% 71.71% 0.000102
Logistic
regression
Accuracy 83.18% 80.61% 84.87% 0.000087
Recall 89.75% 79.36% 89.47% 0.000496
Precision 39.69% 31.10% 46.71% 0.001618
F-measure 53.95% 46.15% 60.02% 0.001217
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
1:1 1:2 1:3
Recall
隨機森林
支援向量機
類神經網路
分類樹
羅吉斯迴歸
• Data preparation
• Introduction of Intelligent Tax Model
• Sampling ratio
and Model
comparison
• Modeling
• Assessment and
Verification
Easy to use
You don’t have
to purchase
statistical software
processing
large data
rapidly
You don’t need
statistics
background
Only need to
connect to the
network
Intelligent Tax Model
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From March 2006, Amazon.com first launched services of cloud computing;the next year, Google proposed the term “cloud computing” formally
“More and more companies is hot pursuit of cloud computing, they all want to fly the cloud“, the former China Netcom CEO, Chairman of China Broadband Capital now, Tian Suning observed.
The latest one, "The Economis" title "war on cloud“ point out Google, Microsoft and Apple competition for the business opportunities of cloud computing
Google is leading position on search engine, but now Microsoft also aware of this change, so they start to put in a lot of resources and ready to catch up.
The data warehouse is the basis for the
development of data mining, but also the support of business intelligence, data mining is also an important part of business intelligence, It says, the data warehouse is a very important role for business intelligence.
The companies most concerned in how to efficient calculation of the mass data with the data reuse and dig in enterprise.
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The hot of cloud computing, let the president of U.S. ,Barack Obama also in on it.
In September this year, the White House chief information officer, Vivek Kundra announced a new government website Apps.Gov which using cloud technology, that will replace the old IT information systems.
According to the New York Times reported, Apps.Gov estimated save seventy-five billion U.S. dollars annually for the U.S. .
Chunghwa Telecom and Microsoft signed a memorandum of cooperation of cloud computing strategic alliance, cooperation will focus on the application of client software services and cloud computing services, that will create a new mode of operation.
This strategic alliance, Chunghwa Telecom will use Microsoft's advanced platform to provide enterprise and consumers the most convenient action added and cloud services, that will help enterprise enhance efficiency and bring convenience and intelligent digital life to consumers.
It represent "cloud services" with computer, phone and TV will towards another mileage in the future
Because of Microsoft cloud platform technology, consulting and Chunghwa Telecom platform integration, sharing of resources and services, consumers and business can experience any time, any place, using any equipment obtain the necessary information and services, and enjoy the convenience of digital life.
TSMC began to build an internal cloud architecture, the company's DT changed to streamline computer (thin client), that not only reduce procurement costs, but also enhance the security of data and reduce the chance of employees leakage and penetration of commercial espionage.
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“Cloud Computing is about to detonate a commercial revolution and rewrite the rules of the game” ,the United States, “BusinessWeek "writes in June 2009.
“Cloud computing make enterprises throttling, and also become creative”, the United States," Harvard Business Review "produced after the turmoil of the times Episode topics, the author analyze in July 2009.
“Cloud computing will be a nimbus, make enterprise more flexible”. And since last October, the " Economist “ in British succession of reported. Recently, cloud computing issues constantly, and not only important in the world of media attention, but also make foreign enterprises more involved.
Smart phone, GPS and other mobile devices, will develop more and more services via cloud computing in the future.
And further, cloud computing can be applied in the biological sciences. For example, the analysis of gene structure, gene mapping sequencing, and resolve the cancer cells. It is much fast and accurate by using cloud computing to assist.
That is, when a large number of information processing is no longer expensive, many technology will come into being.
Security Since the concept of "cloud computing" was proposed, the
problem of security has never subsided. Security problem
consists of two aspects, first is the information will not be
leaked out to cause unnecessary losses, second, ensure
access information is accurate which we need.
In March 2009, the world-
famous company Google had
embarrassed to admit the fact
that careless disclosure private
information of customer, which
also makes people re-examine
safety issues of cloud
computing
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Cloud computing system failure (interruption service of Sidekick, Amazon EC2 has been a denial of service attack, as well as the disruptions of Google email)
Expansion the promotion and application level
The problem of professional ethical and moral issues (legal aspects)
Future of Cloud
Computing
Business Next( 12/20/2011 2:00:59 PM +08:00 )
Energy：
Generation power on their own!
Try to think of the dynamic of our side become a true energy, such as your every action, or tap water flowing through the water pipes, in the future they are likely to convert. IBM scientists have been tested sea wave in the Irish. In the future, people will interception of action to collect by wear a small device.
Security：
No longer need password!
The term "multiple authentication biological characteristics (multifactor biometrics)" sounds very fancy it! Use in the reality of our lives, it is replace the traditional password authentication to retina scan, voiceprint identification. Biological characteristics is the most unique password, that we don’t have to worry about being stolen.
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Mind reading: No longer is just a science movie plot
Pick up the phone call will become obsolete move ! IBM scientists are studying how to link the human brain with a device, such as computers or smart hones. It is possible to think about things in your head into reality in the future. For example, when you see a box on the screen of computer, then you effort to "want" it to move to the left, the box will move to the left. Do not think this is a sci-fi movie, through brainwave detection it may occur. And have the opportunity to use in the rehabilitation or autism treatment.
Mobile: The digital divide no longer exists
Mobile devices is to eliminate the digital divide in remote areas, more and more areas receive information by mobile network . You can see a significant change within five years. IBM is developing new solutions and business models to import mobile commerce and telemedicine.
Analytics ：
Say goodbye to junk mail and messages
Through Data Mining and Cloud Computing will become the most powerful assistant to help you filter junk mail , and provide the part which you need. For example, booking your favorite Concert by combined interest and calendars, suggest the best travel routes depending on the weather conditions.
漫步云端，任重而道远！