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Semantic Web Technology @KMUTNB Seminar 15052014
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Transcript of Semantic Web Technology @KMUTNB Seminar 15052014
Semantic Web and Ontology Engineering : Seminar and Workshop
Dr.Krich Intratip (Peakmaker): PhD. in IT
IT Seminar on 15/05/2014
Agenda IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Fundamental of Semantic Web Technology
Semantic Web application : Development and Challenging
Research trend on Semantic Web
An Ontology Engineering : GT Approach and Tools
Fundamental of Semantic Web Technology
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Introduction IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Semantic Web was introduced
Berners-Lee at the Home Office, London, 2010
T. Berners Lee, J. Hendler and O. Lassila. The Semantic Web. Scientific American, May 2001.
”The Semantic Web is an extension of the current web in which information is given Well-defined meaning, better enabling computers and people to work in cooperation.”
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Semantic Web was introduced
Berners-Lee at the Home Office, London, 2010
The semantic web : an interview with Tim Berners Lee, Consortium Standard Bulletin, 2005. http://www.consortiuminfo.org/bulletins/semanticweb.php
“The semantic web is designed to smoothly interconnect personal information management, enterprise application integration, and the global sharing of commercial, scientific and culture data. We are talking about data here, not human documents.”
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
7
What Is An Ontology?
• Ontology (Socrates & Aristotle 400-360 BC)
• The study of being
• Word borrowed by computing for the explicit description of the conceptualization of a domain: – concepts
– properties and attributes of concepts
– constraints on properties and attributes
– Individuals (often, but not always)
• An ontology defines – a common vocabulary
– a shared understanding
http://www.co-ode.org/resources/tutorials/iswc2005
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Why Develop an Ontology? • To share common understanding of the
structure of descriptive information – among people
– among software agents
– between people and software
• To enable reuse of domain knowledge – to avoid “re-inventing the wheel”
– to introduce standards to allow interoperability
http://www.co-ode.org/resources/tutorials/iswc2005
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Data-Information-Knowledge-Wisdom
Wisdom
Knowledge
Information
Data
Concept Technology
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
2.0 VS 3.0 IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Database App. VS Semantic Web App.
Transaction
• Table & Data
• Relationship for join data
• Query
• Can’t separate domain knowledge from programming code
• Intelligence by human
Semantic
• Concept & Instance
• Relationship create meaning
• Inference
• Domain knowledge independence
• Intelligence by machine
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Triple makes a semantic
Meaning
Subject
Predicate
Object
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Concept & Instance
Concept
instance
instance
instance
instance
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Structural Relations
Class roles Ontology
Super class
Sub class
Is-a
Part-of
Attribute-of
RDF/OWL
Relations
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Semantic Web Stack IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Ontology
OWL
Knowledge Relation of Things
Logic
Database
Data
represents
represents
implemented by
is
is
SWRL
implemented by
applied with
Intelligence
introduces
Semantic Web Technology
is a kind of
is a kind of
Semantic Web Concept IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Group of entities
Class Interested topics Relations
is a
captures from represented by has
Knowledge
has a
Logic
Rules of the knowledge
Knowledge powerful (Intelligence)
is a
increases
has a
Instances
Data items of the concepts or entities
URI
are
referred by stored in
has
referred by
Semantic Web
Domain concept
used by
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
http://semanticweb.org/id/Denny_Vrandecic
URIs / IRIs • URIs are “Uniform Resource Identifiers”
– IRI: Unicode-based “Internationalized Resource Identifiers”
• Every URI identifies one entity
• Semantic Web URIs usually use HTTP – HyperText Transfer Protocol
– Can be resolved to get more data (ideally)
– Linked data
Protocol Domain Local name
thing:Denny_Vrandecic Prefix
Namespace
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
19
Angola
Africa
Zambia
Country
Continent
type
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
20
http://ontoworld.org/id/Angola
http://ontoworld.org/id/Africa
http://ontoworld.org/id/Zambia
Angola
http://www.w3.org/2000/01/rdf-schema#label
Africa
Located in
Zambia
Country
Borders
Continent http://ontoworld.org/id/Category:Country
http://ontoworld.org/id/Category:Continent
http://www.w3.org/1999/02/22/rdf-syntax-ns#type
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
21
http://ontoworld.org/id/Angola
http://ontoworld.org/id/Africa
http://ontoworld.org/id/Zambia
ประเทศแองโกลา
http://www.w3.org/2000/01/rdf-schema#label
ทวปแอฟรกา
แหง
ประเทศแซมเบย
ประเทศ
ชายแดน
ทวป http://ontoworld.org/id/Category:Country
http://ontoworld.org/id/Category:Continent
http://www.w3.org/1999/02/22/rdf-syntax-ns#type
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
22
http://ontoworld.org/id/Angola
http://ontoworld.org/id/Africa
http://ontoworld.org/id/Zambia
Angola
http://www.w3.org/2000/01/rdf-schema#label
Africa
Located in
Zambia
Country
Borders
Continent http://ontoworld.org/id/Category:Country
http://ontoworld.org/id/Category:Continent
http://www.w3.org/1999/02/22/rdf-syntax-ns#type
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Slide 23
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Web 3.0, Semantic Web, Ontology, Linked data
• Web 3.0 เปนยคของเวบ จะเขาใจเรองยคของเวบตองไปดความเปนมาจาก Web
1.0(Hyperlink-Web of documents) -> Web 2.0(Social, Collaborative, Networking Web) ->Web 3.0(Intelligent Web, Web of linked data) ซงแตละยคกเนนประโยชนการใชงานเวบไปคนละอยาง
• Semantic Web เปนเทคโนโลยหนงของ Web 3.0 ทวาดวยเวบเชงความหมายทคอมพวเตอรสามารถอานแลวรบรได(machine readable) เทยบเคยงคลายกบ SOA ทเปนเทคโนโลยหนงของ Web 2.0
• Ontology เปน main component ของ Semantic Web หมายความวาหากไมม ontology แลวกจะไมเกด Semantic Web นนเอง แต ontology ไมใชทงหมดของ Semantic Web แคองคประกอบหลกเทานน
• Linked data เปนลกษณะหนงหรอแนวทางหนงในการ implement ตว Semantic Web แนนอนทสดแลวสงทอยเบองหลงมนกคอ ontology นนเอง
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Knowledge representation and Ontology
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Semantic Web application
Development and Challenging
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
กระบวนการจดการความร (KM Processes)
Structuring Knowledge
ดร.มารต บรณรช, Ontology for Information System Design and Development, 28 พฤศจกายน 2553
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
สงทตองรในการสราง Ontology
หนาตาของความรทน ามาสรางเปน Ontology เปนอยางไร?
ใครคอ Domain experts(ตวจรงทเปนตวแทนประชากรได)/Stakeholders?
Intend to use
กระบวนการตรวจสอบความถกตอง
• ความรทน ามาท าเปน Ontology
• Well-formed Design of ontology
Ontology improvement
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
กระบวนการพฒนา Ontology
http://protege.stanford.edu/publications/ontology_development/ontology
101-noy-mcguinness.html
Natalya F. Noy and Deborah L. McGuinness , Ontology Development 101:
A Guide to Creating Your First Ontology, Stanford University, Stanford, CA,
94305
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Some of ontology (re)-engineering processes (Knowledge extraction)
• Define topic area – หวขอทสนใจคออะไร?
• Define domain specific – ประเดนทสนใจในหวขอนนทตองการใหความหมายหรอการอธบายคออะไร?
• Define intend to use (Domain expert) – การใหความหมายหรอการอธบายนนเพอวตถประสงคใด?
• Breakdown into sub-domains/concepts – กลมแนวความคดยอยหรอความหมายกลมยอยคออะไรบาง?
– Review literature (Consider reuse)
• Define indicators in each concept
• Define indicator measurement
• Define scale of the measurement
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Instrument & Ontology design
Domain
Intend to use
Concept 1
Concept 2
Att. 1 Att. 2 Att. 3 Att. 4 Att. 5 String Int
ตวบงชนามธรรม
ตวบงชสงเกตได
มาตรวด ขอบเขต
ใหความหมาย
ในสงทตองการ อธบาย
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Principle of defining class and its relation
• Class (นามธรรมทตองการการอธบาย)
– ม class node อย 2 ประเภท • Concept node ควรตองไดรบการอธบายเพมเตมจาก node อน
– กฎ : ไมสามารถเปนทอยของ Instance ได
• Attribute node ควรตองไดรบการอธบายเพมเตมดวยการใส Instance
– กฎ : เปนทอยของ Instance
– มความสมพนธระหวาง concept node ไดสองแบบ • Is-a, Part-of
– มความสมพนธระหวาง concept node กบ Attribute node ไดแบบเดยว คอ Attribute-of
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Principle of defining instance and its relation
• Instance (data item) – กฎ : ตองถกบรรจอยใน Attribute node
• One fact in one place
• Atomic value
• Relation – กบ Attribute node เปน Instance-of
– ระหวาง Instance อนใน Attribute node อนจะเปน Has_???
• เขาใจธรรมชาตของ Instance วาสามารถเจรญเตมโตไปเปน Node ไดเมอมการเปลยนแปลงจ าเปนตอง re-structure ontology
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Class/Instance and their relations
concept
concept
concept
concept
concept
attribute
Is-a Part-of Att-of
Ins-of
parent
child
Intrinsic/Concrete VS Extrinsic/Logical
instance
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
INFERENCE ? QUERY & RULE
35
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Inference and Decision
• ขอเทจจรง – ความสง(m)
– น าหนก(kg)
• เกดคณสมบตตามมา (Query) – BMI = น าหนก(kg) / ความสง(m) ยกก าลงสอง
• การอนมาน – ใชเกณฑมาตดสน หรอการใหความหมาย
http://en.wikipedia.org/wiki/First-order_logic
http://www.chulabook.com/description.asp?barcode=978974
0326960
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
การท าอนมาน
ภาวะ คาดชนความหนาทค านวณได ผอม ระดบ 4 < 16.0 ผอม ระดบ 3 16.0-16.9 ผอม ระดบ 2 17.0-18.4 ผอม ระดบ 1 18.5-19.9 ปกต 20.0-24.9 อวน ระดบ1 25.0-29.9 อวน ระดบ 2 30.0-39.9 อวน ระดบ 3 > 40.0
http://www.thailabonline.com/BMI.htm
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
หลกการส าคญในการออกแบบ Ontology
• พจารณาความละเอยดหยาบของสงทตองการอธบาย และใหแตละระดบของการอธบายมความละเอยดหยาบพอๆกน (Generic VS Specific)
• ปกตแลว Ontology ใชหลกการจดกลมจดประเภทขอมลหรอกลมแนวคด เปนหมวดหม (Taxonomy) เปน Hierarchy แลวใช First order logic ในการอนมานความหมาย ซงความหมายจะไมคลมเครอถาหากขอมลหรอกลมแนวคดนนมอยทเดยว(Unique) ในโครงสราง Ontology
• จะเพมความสามารถในการ Reuse ใหกบ Ontology ได โดยท าให Ontology นนมความหมายชดเจนอยางใดอยางหนงตามเจตนารมณการใชงาน
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Ontology quality attributes
• Business (Usage) Objectives and scope must be clearly identified
• Knowledge must be reliable
• Knowledge must be accessible and available
• Knowledge must be shared and integrated seamlessly
intention reliable
sources/processes
Web technology and triple
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Knowledge & Ontology development life cycle
Describe domain and
intend to use
Instrument development
Gather information
Build up domain
knowledge
Practice based
ontology design
Inference over
ontology
meaning
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Maintenance and performance problems
Hard to maintenance
Domain knowledge is in both its
ontology and its programming code
One fact is in many places
Lack of performance
Ontology is too big
Unnecessary nodes or instances
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Goals
Easy to maintenance
Increase performance
Ontology improvement
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Domain knowledge is in both the ontology and its programming code
• Not only programming problem but also ontology design problem
• Domain knowledge should be in ontology and should not be in programming code
• Hard to maintain the ontology (adding, deleting, removing, modifying)
• Blur in domain and range of the attribute
• Cause to composite value
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Example of composite value
Black color Label
Black Label Red Label
Black box, color of box is black
Red Box, color of box is red
Black t-shirt, color of t-shirt is black
Product name
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Example of composite value
Black color Label
Black Label Red Label
Black box, color of box is black
Red Box, color of box is red
Black t-shirt, color of t-shirt is black
Product name
Composite value Non-composite value
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Example of composite value
Black color Label
Black Label Red Label
Black box, color of box is black
Red Box, color of box is red
Black t-shirt, color of t-shirt is black
Product name
It is a design problem issue, not only programming problem issue.
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Some domain knowledge are thrown in Programming area
Composite value
Ontology area
Programming area “Bla
ck b
ox”
“Black box”
Black
Box
Separate to
What does it mean?
What is the box color?
What is the item?
for
for
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Optimizing Rules
• Step-wise approach for improving for ontology design – 4 optimizing rules
• Remove composite-values to optimize the maintenance
• Remove one fact in many places to optimize the maintenance
• Remove unused class to optimize the performance • Remove unnecessary class to optimize the
maintenance and performance
“Optimize both the maintenance and performance”
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Research trend on Semantic Web
Berners-Lee says the next big thing for changing and
understanding the world, and the next big thing for the
internet, is the ability to access whatever data we need,
whenever we need it. By connecting our data together
we can solve world problems and make life easier.
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Web Technology Trend IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Research trend Semantic Search
•New Google
•Helpdesk
Recommendations
•DSS
•suggestion
Personalized assistant
•Meeting
•Planning
•Living
•Personalize
Business intelligent
•Education/Library
•Healthcare
•Advertisement
•CRM
Linked data
•Large scale/Big data
•Semantic based CMS
•Multimedia
Geo-based
•Military
•Agriculture
•Infrastructure
Knowledge engineering Knowledge grid Knowledge repository NLP
Knowledge as Service Knowledge transformation Cloud computing
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Linked-data : Method
Collabora-ting
Sharing Using Adjusting Genera-
ting Training
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Semantic-Based Geo
Geo
Event
Person Time
Object Transaction
http://www.geonames.org/
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Ontology engineering
60
7 ontology design problems (150 samples from in-depth interview)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Structure
Redundancy
Composite value
InferencePerformance
Reusablility
Maintainablility
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Ontology building problems (150 samples from in-depth interview)
7
problems
Design Knowledge acquisition
87% 100%
Solved 67% Solved 7%
Design principle
Sources Extraction method
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Research problems • Ontology is not reliable
Problems
Mistake on ontology design
Ontology is not fit Mistake on knowledge
extraction process
Semantic Web development
Semantic Web application performance
Reliability on Semantic Web application
Impact
Impact Impact
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
An example of relevance theory 56/20 หม 5 ต.ปลายบาง อ.บางกรวย จ.นนทบร 11130
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Ontology study
Ontology study AI
Knowledge representation
Description logic
Meaning of ontology
RDF OWL SWRL Ontology development
Ontology engineering
Ontology design
Ontology improvement
Semantic web
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Business rule approach
• List business rules using If-Then format and align them
• Identify nodes(concept and attribute) and their relations
• Group rules within nodes
• Identify Usecase
• Create procedure
• Create OWL using nodes and their relations
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Scenario
• Case : OO-Programming expert
• Need to know who are the expert in OO-Programming though, the system has no related information about OO in knowledgebase
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
List business rules
• If the man know C++ then imply that the man knows OO • If the man know C# then imply that the man knows OO • If the man know Java then imply that the man knows OO
• If the man know C then imply that the man knows Structure programming • If the man know Pascal then imply that the man knows Structure
programming
• If the man know VB then imply that the man knows .Net framework • If the man know C# then imply that the man knows .Net framework
• If the man know PHP then imply that the man knows web programming • If the man know ASP then imply that the man knows web programming • If the man know JSP then imply that the man knows web programming
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Identify nodes(concept and attribute)
• Concept nodes – Person
• Attribute nodes – Name – Programming skills
• Instances – C++ – C# – Java – C – Pascal – PHP – ASP – JSP
– IT Knowledge • OO • .Net framework • Structure programming • Web programming
• Relation – Name (att-of) Person – Programming skills (att-of) Person – Name (has_Skills) Programming skills
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Group rules and nodes
• G#1 : Who knows OO (Name has_skills Programming skills) – If the man know C++ then imply that the man know OO – If the man know C# then imply that the man know OO – If the man know Java then imply that the man know OO
• G#2 : Who knows structure programming (Name has_skills Programming skills) – If the man know C then imply that the man know Structure programming – If the man know Pascal then imply that the an know Structure programming
• G#3 : Who knows .Net framework (Name has_skills Programming skills) – If the man know VB then imply that the man know .Net framework – If the man know C# then imply that the man know .Net framework
• G#4 : Who knows web programming (Name has_skills Programming skills) – If the man know PHP then imply that the man know web programming – If the man know ASP then imply that the man know web programming – If the man know JSP then imply that the man know web programming
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Identify Usecase
List person who knows structure
programming
List person who kows OO
List persone who knows .Net
framework
User
List person who knows web
programming
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Create procedure
Start
List imply
options
List OO List
structure P.
List .Net List web P.
End
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Create OWL using nodes and their relations
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Roles and Relationships (ontology improvement)
concept
concept
concept
concept
concept
Is-a Part-of Att-of
Ins-of
Subject
Object
Predicate
attribute
instance
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Relationship assignment
parent node child node relation meaning
concept class node concept class node is-a superset/subset
concept class node concept class node part-of component
concept class node attribute class node attribute-of property
attribute class node instance node instance-of fact
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
ตวอยางการสราง Ontology ตามแนวทาง GT
• Ref. : เอกสารขอมลตวอยาง
OWL: Things
Person
Thai_person Address
Name
Address
Title
Gender
Status
House_no
Tumbol
District Province
Post_code
Somchai
Somporn
Wipoj
Somjit
Jintana
Mr.
Miss
Mrs.
Ms.
male
female single
married
divorce
widowed
100
56
72 Plai-Bang
Bang-Pood
Tale-Chupsorn
Bang-Kruai
Park-Ked
Meuang
Nonthaburi
Lop-Buri
10300
11130
15000
Is_a Is_a
P/o
a/o
a/o
I/o
I/o
I/o
I/o
I/o
I/o
I/o
I/o
I/o
Is_a
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
OWL: Things
Person
Thai_person Address
Name
Address
Title
Status
House_no
Tumbol
District Province
Post_code
Somchai
Somporn
Wipoj
Somjit
Jintana
Mr.
Miss
Mrs.
Ms.
single
married
divorce
widowed
100
56
72 Plai-Bang
Bang-Pood
Tale-Chupsorn
Bang-Kruai
Park-Ked
Meuang
Nonthaburi
Lop-Buri
10300
11130
15000
Is_a Is_a
P/o
a/o
a/o
I/o
I/o
I/o
I/o
I/o
I/o
I/o
I/o
Is_a
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Grounded theory : coding IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
การสราง ontology จาก GTM
Ontology using GT with improvement method
IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
Role assignment Flow IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
RDF-OWL-DL-GT IT Seminar on 15/05/2014 @ KMUTNB : Dr.Krich Intratip
แนะน า Hozo ontology editor
Ref: คมอการใชงาน Hozo-Ontology Editor (NECTEC, 2555)
อานเพมเตม
• คมอการใชงาน Protégé
• การใชงาน SWRL บน Protégé
• Blog : Potheus @http://potheus.blogspot.com/
• Discussion @https://www.facebook.com/groups/zimmaticlab
• ขอเชญชวน รวมงานและสง paper ในงาน International Conference :
the 4th Joint International Semantic Technology
(JIST2014) conference • งานจดวนท 9-11 พ.ย. 2014 ทเชยงใหม ในธม “Open Data and Semantic
Technology” deadline สง paper : 1 ส.ค.2014 • งานนคมมาก ทานจะไดรจกกบนกวชาการ ผเชยวชาญทท างานเกยวกบ Semantic
Web Technology โดยตรง สามารถเขาพดคย ปรกษา หารอ ไดอยางเปนกนเอง (แอบกระซบวาหลายๆ ทานจบการศกษาเพราะทานผเชยวชาญเหลานมาเยอะแลวดงนนอยาพลาดโอกาสทดๆ เชนน)
• นอกจากนทานยงไดมโอกาส workshop กบผพฒนา HoZo : Ontology
Editor Tool โดยตรง (อะไรจะดขนาดน) รายละเอยดเพมเตมท : http://language-semantic.org/jist2014/
ขอขอบคณทกทานครบ ขอเสนอแนะ หรอ ขอซกถาม
Dr.Krich Intratip : Peakmaker
Dr.Sasiporn Usanavasin
FB: Zimmantic lab https://www.facebook.com/groups/zimmaticlab/
FB: SEM Study Lab https://www.facebook.com/groups/SEMStudyLab/