SlideShare uma empresa Scribd logo
1 de 26
Baixar para ler offline
Error-Tolerant RDF Subgraph
Matching for Adaptive Presentation
of Linked Data on Mobile
Luca Costabello
2
Mobile Guide
 Museum Triplestore
“Is it optimized for my tablet?”
“Does it highlight practical
information when I am on my way?”
“Does it have a visually-impaired mode?”
Example: An RDF-based Mobile Guide for Museums
3
How to enable context-aware adaptation
for Linked Data consumption?
Research Challenges
1.  Model context-aware presentation metadata?
2.  Select proper presentation metadata at runtime?
“Context” as in [Dey 2001]
4
Modeling Presentation Metadata
1
Selecting Presentation Metadata
with Error-Tolerant Matching
2
Evaluation
3
Conclusions
4
5
Modeling Presentation Metadata
1
Selecting Presentation Metadata
with Error-Tolerant Matching
2
Evaluation
3
Conclusions
4
6
NAC
Laakko
Chen
Zhang
Chamaleon
Butter
Paternò
MIMOSA
CAMB
Adipat
COIN
CSSMedia
Queries
PRISSMA
(OurSystem)
Linked Data
support
 ✓
Context-awareness
 ✓ ✓
 ✓ ✓ ✓ ✓ ✓
 ✓
Standard Languages
 ✓ ✓ ✓ ✓ ✓
 ✓
 ✓
Runtime adaptation
 ✓ ✓
 ✓
 ✓
Multimodality
 ✓
 
Client-side only

(for privacy preservation)
 ✓ ✓
 ✓
 ✓
 ✓
Evaluation
 ✓ ✓ ✓ ✓
 ✓
Adaptive Presentation Frameworks for the Web
7
Presentation Frameworks for the Semantic Web
Haystack
Noadster
Surrogates
Declarative
approach
 ✓
 ✓
Domain
Independence
 ✓
 ✓
 ✓
Standard Languages
 ✓
 ✓
Context Awareness
Automatic
stylesheets
Evaluation
Distribution
Multimodality
 ✓
Xenon
Tal4Rdf
LESS
Hidethe
Stack
LDVM
✓
 ✓
 ✓
 ✓
 ✓
✓
 ✓
 ✓
✓
 ✓
 ✓
✓
✓
Fresnel
✓
✓
✓
✓
PRISSMA
(OurSystem)
✓
✓
✓
✓
✓
✓
Fresnel [Pietriga et al. 2006]
8
Illustration from [Pietriga et al. 2006]
Content formatting
and additional
content"
Content selection
and ordering"
Styling instructions
for fonts, colors, and
borders"
Presentation Metadata Vocabulary and Rendering Engine for RDF
9
Our Contribution: Extending Fresnel with PRISSMA*
Context
PRISSMA Prism
Context
Description
PRISSMA Context
*Presentation of Resources for Interoperable Semantic and Shareable Mobile Adaptability
Extending Fresnel with PRISSMA
10
Context
fresnel:Lens
fresnel:Format
fresnel:group
fresnel:group
Environment
environment
Device
device
User
user
ns.inria.fr/prissma
fresnel:Group
fresnel:purpose
Fresnel
PRISSMA (Our Contribution)
Contextfresnel:Purpose
Prismfresnel:Group
owl:equivalentClass
fresnel:purpose
owl:equivalentClass
11
Example
A Prism for showing and styling titles and
authors of paintings metadata accessed from
inside the museum.
12
:paintingPrism a prissma:Prism, fresnel:Group ;!
fresnel:stylesheetLink <style.css> ;!
fresnel:purpose :atTheMuseum .!
!
:paintinglens a fresnel:Lens;!
fresnel:group :PaintingPrism ;!
fresnel:classLensDomain art:Painting ;!
fresnel:showProperties (dc:title!
dcn:author) .!
!
:depictionFormat a fresnel:Format ;!
fresnel:group :paintingPrism ;!
fresnel:propertyFormatDomain dc:title ;!
fresnel:valueStyle ”title"^^fresnel:styleClass .!
!
:atTheMuseum a prissma:Context ;!
prissma:environment :museumEnv .!
!
:museumEnv a prissma:Environment ;!
prissma:poi :museumGeo .!
!
:museumGeo geo:lat "48.86034" ;!
geo:long "2.337599" ;!
prissma:radius ”200" .!
Lens
Format
Context
prissma:environment
2.337599
48.86034
200
:museumGeo
geo:lat
geo:long
prissma:radius
prissma:poi
prissma:Environment
prissma:Context
:atTheMuseum
:museumEnv
A Prism for showing and styling titles and authors of
paintings metadata accessed from inside the museum.
Example:
Examples

PRISSMA Browser for Android
13
Smartphone, user walking
in museum town.
Tablet, user at home.
github.com/lukostaz/prissma-browser/
14
Modeling Presentation Metadata
1
Selecting Presentation Metadata
with Error-Tolerant Matching
2
Evaluation
3
Conclusions
4
Selecting Presentation Metadata 
15
:smartphoneMoving
:tabletAtHome
:maleVisitorAtTheMuseum
:actualContext
16
Ambiguity
 Incompleteness
Selecting Presentation Metadata is tricky
Sensor Noise
2.32434
48.843453
:poi
geo:lat
geo:long
10
prissma:radius
2.337599
48.86034 5
:poi
geo:lat
geo:long
prissma:radius
:user1
"computers"
foaf:interest
:user1
"computer science"
foaf:interest
:user1
:Karl :Anita
prissma:nearbyEntity
:John
:user1
:Karl :Anita
prissma:nearbyEntity
Prism
Actual
Need Error-tolerant matching
17
Error-tolerant matching for RDF Graphs
iSPARQL
Silk
Zou
RDF-specific
 ✓
 ✓
 ✓
Data Heterogeneity
Client-side Execution

(for privacy preservation)
Incremental index updates
✓
Selective matching cache
PRISSMA
✓
✓
✓
✓
Messmer
✓
Our Contribution: Adapting Messmer
to RDF and Mobile Context
Optimal error-tolerant subgraph isomorphisms based on graph edit distance.

18
• Atomic element might be
a graph: Context Units
•  Core Context Classes
•  Entities
•  Literals
•  Geo
•  Time
• Customized Cost Functions
•  Strings (Monge-Elkan)
•  Geographic (Haversine distance + Decay)
•  Temporal (Interval Inclusion + Decay)
•  Missing nodes
2.32434
48.843453
:poi
geo:lat
geo:long
10
prissma:radius
Our Extensions:
[Messmer et al. 98]
Prism Selection - Step 1: Decomposition
(i.e. Index Building)
19
prissma:environment
2.337599
48.86034
200
:museumGeo
geo:lat
geo:long
prissma:radius
prissma:poi
prissma:Environment
prissma:Context
:atTheMuseum
:museumEnv
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{3,1,2,{prissma:poi}}
{4,0,3,{prissma:environment}}
:atTheMuseum
Context Units
Prism Selection – Step 2: Online Search Algorithm!
1  foreach context unit S in D do!
2  compute_subgraph_isomorphisms(S,GI)!
3  !
4  while C(fcheapest)< T { !
5  if S1 is Prism then!
6  R.add(S1)!
7  !
8  foreach child of S1 do!
9  fchild= combine(fS1,fS2)!
10  }!
11  return R!
20
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{3,1,2,{prissma:poi}}
{4,0,3,{prissma:environment}}
:atTheMuseum
prissma:environment
2.32434
48.843453
:actualPOI
geo:lat
geo:long
prissma:poi
:ActualCtx
:actualEnv
10
prissma:radius
C=0! C=0.34! C=0!
1. Compute context units
isomorphisms costs
prissma:Context
0 48.86034
-2.337599
200
geo:lat
geo:lon
prissma:radius
1
:museumGeo
prissma:Environment
2
{3,1,2,{prissma:poi}}
{4,0,3,{prissma:environment}}
:atTheMuseum
Prism Selection: Search Algorithm!
1  foreach context unit S in D do!
2  compute_subgraph_isomorphisms(S,GI)!
3  !
4  while C(fcheapest)< T { !
5  if S1 is Prism then!
6  R.add(S1)!
7  !
8  foreach child of S1 do!
9  fchild= combine(fS1,fS2)!
10  }!
11  return R!
21
prissma:environment
2.32434
48.843453
:actualPOI
geo:lat
geo:long
prissma:poi
:ActualCtx
:actualEnv
10
prissma:radius
C=0! C=0.34! C=0!
C=0.17!
C=0.09!
T=0.6!
✓
✓
 ✓
✓
✓
2. Combine costs
C < T --> Match!
22
Modeling Presentation Metadata
1
Selecting Presentation Metadata with
Error-Tolerant Matching
2
Evaluation
3
Conclusions
4
Evaluation: Memory Consumption
23
0
50
100
150
200
250
300
0.1
 0.3
 0.5
 0.7
 0.9
DecompositionItems
Percentage of common context units
Total decomposition Items
Context Units (decomposition)
Context Units (raw prisms)
0
5
10
15
20
25
0.1
 0.3
 0.5
 0.7
 0.9
Memory[KB]
Percentage of common context units
PRISSMA decomposition 
 Jena Models
Evaluation: Response Time
24
If prisms are completely different
 if prisms are highly
similar
→
25
Modeling Presentation Metadata
1
Selecting Presentation Metadata with
Error-Tolerant Matching
2
Evaluation
3
Conclusions
4
26
Limitations and Future Work
Prisms Distribution: 

Linked Presentation Metadata.
Modeling Presentation Metadata
1
Selecting Presentation Metadata
with Error-Tolerant Matching
2
Evaluation
3
 User acceptability evaluation
campaign.
Machine learning to optimize cost
functions parameterization.
Beyond Fresnel: support for other
presentation engines
Thanks.
wimmics.inria.fr/projects/prissma
@lukostaz

Mais conteúdo relacionado

Semelhante a Error-Tolerant RDF Subgraph Matching for Adaptive Presentation of Linked Data on Mobile

How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
4Science
 

Semelhante a Error-Tolerant RDF Subgraph Matching for Adaptive Presentation of Linked Data on Mobile (20)

FAIR Projector Builder
FAIR Projector BuilderFAIR Projector Builder
FAIR Projector Builder
 
Real-time Semantic Web with Twitter Annotations
Real-time Semantic Web with Twitter AnnotationsReal-time Semantic Web with Twitter Annotations
Real-time Semantic Web with Twitter Annotations
 
Atlanta MLconf Machine Learning Conference 09-23-2016
Atlanta MLconf Machine Learning Conference 09-23-2016Atlanta MLconf Machine Learning Conference 09-23-2016
Atlanta MLconf Machine Learning Conference 09-23-2016
 
Chris Fregly, Research Scientist, PipelineIO at MLconf ATL 2016
Chris Fregly, Research Scientist, PipelineIO at MLconf ATL 2016Chris Fregly, Research Scientist, PipelineIO at MLconf ATL 2016
Chris Fregly, Research Scientist, PipelineIO at MLconf ATL 2016
 
Data FAIRport Prototype & Demo - Presentation to Elsevier, Jul 10, 2015
Data FAIRport Prototype & Demo - Presentation to Elsevier, Jul 10, 2015Data FAIRport Prototype & Demo - Presentation to Elsevier, Jul 10, 2015
Data FAIRport Prototype & Demo - Presentation to Elsevier, Jul 10, 2015
 
A Generic Mapping-based Query Translation from SPARQL to Various Target Datab...
A Generic Mapping-based Query Translation from SPARQL to Various Target Datab...A Generic Mapping-based Query Translation from SPARQL to Various Target Datab...
A Generic Mapping-based Query Translation from SPARQL to Various Target Datab...
 
JGrass and uDig, chronicles of a lovestory
JGrass and uDig, chronicles of a lovestoryJGrass and uDig, chronicles of a lovestory
JGrass and uDig, chronicles of a lovestory
 
The nature.com ontologies portal: nature.com/ontologies
The nature.com ontologies portal: nature.com/ontologiesThe nature.com ontologies portal: nature.com/ontologies
The nature.com ontologies portal: nature.com/ontologies
 
Bootstrap Custom Image Classification using Transfer Learning by Danielle Dea...
Bootstrap Custom Image Classification using Transfer Learning by Danielle Dea...Bootstrap Custom Image Classification using Transfer Learning by Danielle Dea...
Bootstrap Custom Image Classification using Transfer Learning by Danielle Dea...
 
#DHNord2019 : Pour un regard à 360 degrés des corpus visuels : pratiques de m...
#DHNord2019 : Pour un regard à 360 degrés des corpus visuels : pratiques de m...#DHNord2019 : Pour un regard à 360 degrés des corpus visuels : pratiques de m...
#DHNord2019 : Pour un regard à 360 degrés des corpus visuels : pratiques de m...
 
bridging formal semantics and social semantics on the web
bridging formal semantics and social semantics on the webbridging formal semantics and social semantics on the web
bridging formal semantics and social semantics on the web
 
Unlocking the Semantics of Multimedia Presentations in the Web with the Multi...
Unlocking the Semantics of Multimedia Presentations in the Web with the Multi...Unlocking the Semantics of Multimedia Presentations in the Web with the Multi...
Unlocking the Semantics of Multimedia Presentations in the Web with the Multi...
 
Getty Vocabulary Program LOD: Ontologies and Semantic Representation
Getty Vocabulary Program LOD: Ontologies and Semantic RepresentationGetty Vocabulary Program LOD: Ontologies and Semantic Representation
Getty Vocabulary Program LOD: Ontologies and Semantic Representation
 
Querying the Web of Data
Querying the Web of DataQuerying the Web of Data
Querying the Web of Data
 
ResearchSpace Platform in Use
ResearchSpace Platform in UseResearchSpace Platform in Use
ResearchSpace Platform in Use
 
The SPARQL Anything project
The SPARQL Anything projectThe SPARQL Anything project
The SPARQL Anything project
 
Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM) ...
 Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM) ... Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM) ...
Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM) ...
 
How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
How to enhance your DSpace repository: use cases for DSpace-CRIS, DSpace-RDM,...
 
Framester and WFD
Framester and WFD Framester and WFD
Framester and WFD
 
PointNet
PointNetPointNet
PointNet
 

Mais de Luca Costabello

Linked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
Linked Data Access Goes Mobile: Context Aware Authorization for Graph StoresLinked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
Linked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
Luca Costabello
 

Mais de Luca Costabello (6)

Machine Learning on Knowledge Graphs: a Quick Tour of Knowledge Graph Embeddings
Machine Learning on Knowledge Graphs: a Quick Tour of Knowledge Graph EmbeddingsMachine Learning on Knowledge Graphs: a Quick Tour of Knowledge Graph Embeddings
Machine Learning on Knowledge Graphs: a Quick Tour of Knowledge Graph Embeddings
 
Traffic Analytics for Linked Data Publishers
Traffic Analytics for  Linked Data PublishersTraffic Analytics for  Linked Data Publishers
Traffic Analytics for Linked Data Publishers
 
Access Control for HTTP Operations on Linked Data
Access Control for HTTP Operations on Linked DataAccess Control for HTTP Operations on Linked Data
Access Control for HTTP Operations on Linked Data
 
Linked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
Linked Data Access Goes Mobile: Context Aware Authorization for Graph StoresLinked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
Linked Data Access Goes Mobile: Context Aware Authorization for Graph Stores
 
PRISSMA, Towards Mobile Adaptive Presentation of the Web of Data
PRISSMA,Towards Mobile Adaptive Presentation of the Web of DataPRISSMA,Towards Mobile Adaptive Presentation of the Web of Data
PRISSMA, Towards Mobile Adaptive Presentation of the Web of Data
 
Time Based Cluster Analysis for Automatic Blog Generation
Time Based Cluster Analysis for Automatic Blog GenerationTime Based Cluster Analysis for Automatic Blog Generation
Time Based Cluster Analysis for Automatic Blog Generation
 

Último

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 

Último (20)

Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdf
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source Milvus
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 

Error-Tolerant RDF Subgraph Matching for Adaptive Presentation of Linked Data on Mobile

  • 1. Error-Tolerant RDF Subgraph Matching for Adaptive Presentation of Linked Data on Mobile Luca Costabello
  • 2. 2 Mobile Guide Museum Triplestore “Is it optimized for my tablet?” “Does it highlight practical information when I am on my way?” “Does it have a visually-impaired mode?” Example: An RDF-based Mobile Guide for Museums
  • 3. 3 How to enable context-aware adaptation for Linked Data consumption? Research Challenges 1.  Model context-aware presentation metadata? 2.  Select proper presentation metadata at runtime? “Context” as in [Dey 2001]
  • 4. 4 Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 Conclusions 4
  • 5. 5 Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 Conclusions 4
  • 6. 6 NAC Laakko Chen Zhang Chamaleon Butter Paternò MIMOSA CAMB Adipat COIN CSSMedia Queries PRISSMA (OurSystem) Linked Data support ✓ Context-awareness ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Standard Languages ✓ ✓ ✓ ✓ ✓ ✓ ✓ Runtime adaptation ✓ ✓ ✓ ✓ Multimodality ✓ Client-side only
 (for privacy preservation) ✓ ✓ ✓ ✓ ✓ Evaluation ✓ ✓ ✓ ✓ ✓ Adaptive Presentation Frameworks for the Web
  • 7. 7 Presentation Frameworks for the Semantic Web Haystack Noadster Surrogates Declarative approach ✓ ✓ Domain Independence ✓ ✓ ✓ Standard Languages ✓ ✓ Context Awareness Automatic stylesheets Evaluation Distribution Multimodality ✓ Xenon Tal4Rdf LESS Hidethe Stack LDVM ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Fresnel ✓ ✓ ✓ ✓ PRISSMA (OurSystem) ✓ ✓ ✓ ✓ ✓ ✓
  • 8. Fresnel [Pietriga et al. 2006] 8 Illustration from [Pietriga et al. 2006] Content formatting and additional content" Content selection and ordering" Styling instructions for fonts, colors, and borders" Presentation Metadata Vocabulary and Rendering Engine for RDF
  • 9. 9 Our Contribution: Extending Fresnel with PRISSMA* Context PRISSMA Prism Context Description PRISSMA Context *Presentation of Resources for Interoperable Semantic and Shareable Mobile Adaptability
  • 10. Extending Fresnel with PRISSMA 10 Context fresnel:Lens fresnel:Format fresnel:group fresnel:group Environment environment Device device User user ns.inria.fr/prissma fresnel:Group fresnel:purpose Fresnel PRISSMA (Our Contribution) Contextfresnel:Purpose Prismfresnel:Group owl:equivalentClass fresnel:purpose owl:equivalentClass
  • 11. 11 Example A Prism for showing and styling titles and authors of paintings metadata accessed from inside the museum.
  • 12. 12 :paintingPrism a prissma:Prism, fresnel:Group ;! fresnel:stylesheetLink <style.css> ;! fresnel:purpose :atTheMuseum .! ! :paintinglens a fresnel:Lens;! fresnel:group :PaintingPrism ;! fresnel:classLensDomain art:Painting ;! fresnel:showProperties (dc:title! dcn:author) .! ! :depictionFormat a fresnel:Format ;! fresnel:group :paintingPrism ;! fresnel:propertyFormatDomain dc:title ;! fresnel:valueStyle ”title"^^fresnel:styleClass .! ! :atTheMuseum a prissma:Context ;! prissma:environment :museumEnv .! ! :museumEnv a prissma:Environment ;! prissma:poi :museumGeo .! ! :museumGeo geo:lat "48.86034" ;! geo:long "2.337599" ;! prissma:radius ”200" .! Lens Format Context prissma:environment 2.337599 48.86034 200 :museumGeo geo:lat geo:long prissma:radius prissma:poi prissma:Environment prissma:Context :atTheMuseum :museumEnv A Prism for showing and styling titles and authors of paintings metadata accessed from inside the museum. Example:
  • 13. Examples
 PRISSMA Browser for Android 13 Smartphone, user walking in museum town. Tablet, user at home. github.com/lukostaz/prissma-browser/
  • 14. 14 Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 Conclusions 4
  • 15. Selecting Presentation Metadata 15 :smartphoneMoving :tabletAtHome :maleVisitorAtTheMuseum :actualContext
  • 16. 16 Ambiguity Incompleteness Selecting Presentation Metadata is tricky Sensor Noise 2.32434 48.843453 :poi geo:lat geo:long 10 prissma:radius 2.337599 48.86034 5 :poi geo:lat geo:long prissma:radius :user1 "computers" foaf:interest :user1 "computer science" foaf:interest :user1 :Karl :Anita prissma:nearbyEntity :John :user1 :Karl :Anita prissma:nearbyEntity Prism Actual Need Error-tolerant matching
  • 17. 17 Error-tolerant matching for RDF Graphs iSPARQL Silk Zou RDF-specific ✓ ✓ ✓ Data Heterogeneity Client-side Execution
 (for privacy preservation) Incremental index updates ✓ Selective matching cache PRISSMA ✓ ✓ ✓ ✓ Messmer ✓
  • 18. Our Contribution: Adapting Messmer to RDF and Mobile Context Optimal error-tolerant subgraph isomorphisms based on graph edit distance. 18 • Atomic element might be a graph: Context Units •  Core Context Classes •  Entities •  Literals •  Geo •  Time • Customized Cost Functions •  Strings (Monge-Elkan) •  Geographic (Haversine distance + Decay) •  Temporal (Interval Inclusion + Decay) •  Missing nodes 2.32434 48.843453 :poi geo:lat geo:long 10 prissma:radius Our Extensions: [Messmer et al. 98]
  • 19. Prism Selection - Step 1: Decomposition (i.e. Index Building) 19 prissma:environment 2.337599 48.86034 200 :museumGeo geo:lat geo:long prissma:radius prissma:poi prissma:Environment prissma:Context :atTheMuseum :museumEnv prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 {3,1,2,{prissma:poi}} {4,0,3,{prissma:environment}} :atTheMuseum Context Units
  • 20. Prism Selection – Step 2: Online Search Algorithm! 1  foreach context unit S in D do! 2  compute_subgraph_isomorphisms(S,GI)! 3  ! 4  while C(fcheapest)< T { ! 5  if S1 is Prism then! 6  R.add(S1)! 7  ! 8  foreach child of S1 do! 9  fchild= combine(fS1,fS2)! 10  }! 11  return R! 20 prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 {3,1,2,{prissma:poi}} {4,0,3,{prissma:environment}} :atTheMuseum prissma:environment 2.32434 48.843453 :actualPOI geo:lat geo:long prissma:poi :ActualCtx :actualEnv 10 prissma:radius C=0! C=0.34! C=0! 1. Compute context units isomorphisms costs
  • 21. prissma:Context 0 48.86034 -2.337599 200 geo:lat geo:lon prissma:radius 1 :museumGeo prissma:Environment 2 {3,1,2,{prissma:poi}} {4,0,3,{prissma:environment}} :atTheMuseum Prism Selection: Search Algorithm! 1  foreach context unit S in D do! 2  compute_subgraph_isomorphisms(S,GI)! 3  ! 4  while C(fcheapest)< T { ! 5  if S1 is Prism then! 6  R.add(S1)! 7  ! 8  foreach child of S1 do! 9  fchild= combine(fS1,fS2)! 10  }! 11  return R! 21 prissma:environment 2.32434 48.843453 :actualPOI geo:lat geo:long prissma:poi :ActualCtx :actualEnv 10 prissma:radius C=0! C=0.34! C=0! C=0.17! C=0.09! T=0.6! ✓ ✓ ✓ ✓ ✓ 2. Combine costs C < T --> Match!
  • 22. 22 Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 Conclusions 4
  • 23. Evaluation: Memory Consumption 23 0 50 100 150 200 250 300 0.1 0.3 0.5 0.7 0.9 DecompositionItems Percentage of common context units Total decomposition Items Context Units (decomposition) Context Units (raw prisms) 0 5 10 15 20 25 0.1 0.3 0.5 0.7 0.9 Memory[KB] Percentage of common context units PRISSMA decomposition Jena Models
  • 24. Evaluation: Response Time 24 If prisms are completely different if prisms are highly similar →
  • 25. 25 Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 Conclusions 4
  • 26. 26 Limitations and Future Work Prisms Distribution: 
 Linked Presentation Metadata. Modeling Presentation Metadata 1 Selecting Presentation Metadata with Error-Tolerant Matching 2 Evaluation 3 User acceptability evaluation campaign. Machine learning to optimize cost functions parameterization. Beyond Fresnel: support for other presentation engines Thanks. wimmics.inria.fr/projects/prissma @lukostaz