Semantic-based modelling and representation of patrimony ...
Semantic - Enhanced Community Modelling to Support Knowledge Sharing
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Transcript of Semantic - Enhanced Community Modelling to Support Knowledge Sharing
School of somethingFACULTY OF OTHER
School of ComputingFACULTY OF ENGINEERING
Semantic - Enhanced Community Modelling to Support Knowledge Sharing
Kleanthous Styliani
www.comp.leeds.ac.uk/stellak
School of ComputingFACULTY OF ENGINEERING
Oct 30th 2007 Reading Group Session
Overview
•This Research•Algorithms•Study•Initial Results
•Community•Relationship Model•Centrality•Individual User Model
This Research…
Research Focus:Provide holistic personalised support in VC
Main Assumptions:
• Providing adaptation tailored to the community as a whole will help the community function better.
• By promoting the building of TM, development of SMM, and establishment of CCs and identifying CCen inside the community, will improve the functioning of this community
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
This Research…
Research Questions
R1: How to extract a computational model to represent the functioning and evolution of the community as a whole, using semantically enhanced tracking data?
R2: Using that model, how to provide personalised functionality to support the development of TM, building of SMM, establishment of CCs and identification of CCen?
R3: How can personalised support of the above processes affect the functioning of the community?
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
TM
CCs
CCen
SMM
Community Model
Com
mun
ity M
odel
Acq
uisi
tion
Com
munity M
odel Application
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
The Example Community - BSCW
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Oct 30th 2007 Reading Group Session
Input Formalisation…ENVIRONMENT E: <HF, F, R, M, D>
Folder F:
HF : Taxonomy of Folders
<FTitle, FCreator, FDescription, FDate>
Resource R: <RCreatedData, RMetadata>
RCreatedData: <RFolder, RName, RDescription, RRating, RCreator, RDate, RAssessor, RReader>
RMetadata: <RTitle, RAuthor, RSource, RKeywords, RDatePublish>
Based on Dublin Core Metadata element set
Member M: <MName, MEmail, MDateJoin>
This Research
Algorithms
Study
Initial Results
Community Model
Relationships Model
User Interests Participation
Cognitive Centrality
Relationships Personal Hierarchies
ReadRes
InterestSim
UploadSim
ReadDisc
Individual User Models
Community Context
Popular Topics
Peripheral Topics
Cognitively Central
Members
ReadSim
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Modelling Relationships…
ReadResRelationship because A read resources uploaded by B
σ ( , )i jr rN ReadRes i j
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ri
ReadRes i j V
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n321 cccc .....NN,N,N:T
WordNet
irV
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Modelling Relationships…
ReadSim & UploadSimReadSim: Relationship because A reads resources similar to those B reads.
UploadSim: Relationship because A uploads resources similar to those B uploads.
( , )( , )i jr r i j
c csimV Sim N N
n321 cccc .....NN,N,N:T
( , )i jr rsimReadSim V
iCN j
CN
WordNet
i jr rsimV( , )
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Modelling Relationships…
InterestSimSimilarity between two members’ interests
ii kσk),w(L IΙ
),Sim(mInterestSi ji
WordNet
i jSim( , )
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Capturing Centrality…
5
1 1
( ) α ( , )n
D zi z
C j i j
mnMi
ReadRes
ReadSim
UploadSim
InterestSim
ReadDisc 1n
,aC
n
1iki
(pk)
ppD
This Research
Algorithms
Study
Initial Results
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•Run from Oct 2005 – Dec 2006
•BSCW data anonymised & converted into .txt
•Extracted data using Java
•Data stored on a MySQL Database
•Input to algorithms to extract the Community Model
This Research
Algorithms
Study
Initial Results
The Study…
Oct 30th 2007 Reading Group Session
Members 34
Isolates 8
Only uploading 4
Only downloading 13
Uploading & Downloading 9
Total Resources Uploaded 244
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Overview…
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Members
No.
of R
esou
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Uploading Dow nloading
Activity…
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Uploading…
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020406080
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Members
No.
of R
esou
rces
01/10/2005 - 31/12/2005 01/01/2006 - 28/02/200601/03/2006 - 31/05/2006 01/06/2006 - 31/08/200601/09/2006 - 31/12/2006
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Downloading…
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0
10
20
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50
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334
Members
No.
of R
esou
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01/10/2005 - 31/12/2005 01/01/2006 - 28/02/2006 01/03/2006 - 31/05/200601/06/2006 - 31/08/2006 01/09/2006 - 31/12/2006
Initial Results•Community•Relationship Model•Centrality•Individual User Model
ReadRes…
Oct 30th 2007 Reading Group Session
Support:
•Identify complementary knowledge
•Who holds information I am interested in?
Improve TM
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Reading Only…
Oct 30th 2007 Reading Group Session
Have ReadRes with the same members
Support:
•Identify people who are interested in what I am interested.
Encourage Collaboration
-Building SMM
-Improve TM
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Member 5
Oct 30th 2007 Reading Group Session
Member 2 Member 9
Only downloading
Have exactly the same ReadRes relations
Support:
•Encourage collaboration
•Motivate contribution
Initial Results•Community•Relationship Model•Centrality•Individual User Model
ReadSim…
Oct 30th 2007 Reading Group Session
•Support:
•Identify relationships that members are not aware of
•Who is reading resources similar to those I am reading?
•Who is interested in similar resources as I am?
Improve TM
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Oct 30th 2007 Reading Group Session
Reading resources from the same people
Support:
•Develop awareness of this similarity
Improve TM/SMM
Encourage collaboration
Facilitate knowledge Sharing
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Oct 30th 2007 Reading Group Session
UploadSim…
Very strongly connected
Support:
•Identify people who are not uploading & encourage them to contribute
•Make people aware of their similarities
Improve SMM/TM
Support Collaboration
Initial Results•Community•Relationship Model•Centrality•Individual User Model
InterestSim…
Oct 30th 2007 Reading Group Session
Support:
•Identify interest similarity & complementarities
•Who has interests similar to a given member?
Motivate contribution
Encourage collaboration
Improve SMM/TM
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Cognitive Centrality…
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5
10
15
20
25
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334Members
Support:
Where important knowledge is located?
Where unique knowledge is located?
Improves TM/SMM
Motivation mechanism
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Oct 30th 2007 Reading Group Session
Member 12 uploaded only one resource
29.4% of the community read his resource
Support:
•Display similar members, motivate to contribute/ read
•Use ReadSim to motivate
Improve TM/SMM
ReadRes Ego Network UploadSim Ego Network
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Newcomer Integration…
Oct 30th 2007 Reading Group Session
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01/10/2005 -31/12/2005
01/01/2006 -28/02/2006
01/03/2006 -31/05/2006
01/06/2006 -31/08/2006
01/09/2006 -31/12/2006
Uploading Dow nloading
ReadRes Ego Network of Member 19
Support:
•Use ReadRes to help member integrate.
•Who holds knowledge important to this member?
Improve TM
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Member 33 uploaded 11 resources
Never read a resource
Support:
•Help members like 33 to integrate
•Identify similar members & motivate this member to contribute
Improve TM/SMM
Encourage Collaboration
Support Newcomer IntegrationOct 30th 2007 Reading Group Session
Ego Network
UploadSim & InterestSim Ego Network
Integration Problem…
Initial Results•Community•Relationship Model•Centrality•Individual User Model
Future Work…
•Ontology integration
• What will it be different?
•Community model evaluation
•Model community changes over time
• Relationships
• Individual
•Extend an existing system
•Evaluation with users
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results
Summary…
•TM, SMM, CCen can be used to support Virtual Communities
•Modelling semantic-enhanced relationships can help us to identify what support is needed
•A holistic support may provide the foundations for a sustainable virtual community
Oct 30th 2007 Reading Group Session
This Research
Algorithms
Study
Initial Results