This document describes a Linked Data-driven approach for enabling interactions between smart space components and end users. It presents a reference platform architecture that uses semantic annotation, recommendation systems, and user-generated content management to retrieve and enrich information about smart space components from the Linked Data Cloud. An evaluation of the approach is implemented through a tourism use case in St. Petersburg, Russia involving recommendations of local points of interest.

1. 1
Oscar Rodriguez Rocha
Cristhian Figueroa
Iacopo Vagliano
Boris Moltchanov
Linked Data-Driven Smart Spaces

2. 2
Outline
1. Introduction
2. Reference platform and use case
3. Evaluation
4. Conclusion

3. 3
Linked Data Cloud

4. 4
Context
● Information about Smart Space components in
Linked Data Cloud
● Increasing number of mobile devices and their
capabilities
● Improvements in content generation on-the-go
(mobile UGC)
● Critical to provide to end user right information
in the right moment

5. 5
Aims
1. Linked Data based approach for
a) Enabling interactions among Smart
Space components
b) Enabling interactions Smart Space
component – end user
c) Retrieving and enriching information
about Smart Space components
2. Practical application of the approach

6. 6
Architecture
Recommender
System
UGC
Manager
Semantic
Annotator
Reference platform
DBpedia

7. 7
Linked Data-Driven Recommender Systems
● Suggest items to users
– Linked Data-based similarity
– Three types
● Hierarchical
● Transversal
● Hybrid

8. 8
Recommendation Algorithm
Ranked set of items
(classified by categories)
Item (URI)

9. 9
Recommendation Algorithm
Category
Extraction
Ranked set of items
(classified by categories)
Item (URI)

10. 10
Recommendation Algorithm
Category
Extraction
Subcategory
Extraction
Ranked set of items
(classified by categories)
Item (URI)

11. 11
Recommendation Algorithm
Category
Extraction
Subcategory
Extraction
Item
Extraction
Ranked set of items
(classified by categories)
Item (URI)

12. 12
Recommendation Algorithm
Category
Extraction
Subcategory
Extraction
Item
Extraction
Item -
category
Mapping
Ranked set of items
(classified by categories)
Item (URI)

13. 13
Recommendation Algorithm
Category
Extraction
Subcategory
Extraction
Item
Extraction
Item -
category
Mapping
Transversal
Similarity
Calculation
Ranked set of items
(classified by categories)
Item (URI)

14. 14
Recommendation Algorithm
Category
Extraction
Subcategory
Extraction
Item
Extraction
Item -
category
Mapping
Transversal
Similarity
Calculation
Categorization
and
Ranking
Ranked set of items
(classified by categories)
Item (URI)

15. 15
Use Case
Peter and Paul fortress
Hermitage Museum
St. Isaac's Cathedral
St. Petersburg Smart Space

16. 16
Use Case
Peter and Paul fortress
Hermitage Museum
St. Isaac's Cathedral
St. Petersburg Smart Space
DBpedia information +

17. 17
Use Case
Peter and Paul fortress
Hermitage Museum
St. Isaac's Cathedral
St. Petersburg Smart Space

18. 18
Execution Time

19. 19
Candidate Items

20. 20
Conclusion
1. Linked Data based approach to
manage Smart Space components
information
2. Enrich information about Smart
Space components
3. eToursim use case implemented
with Telecom Italia

21. 21
большое спасибо

22. 22
Future Works
● Accuracy evaluation
● Integration of FI-WARE Context Management
GE (context broker)
● Addition of smart space components in Linked
Data cloud
● Additional use cases (museum)

23. 23
Accuracy Evaluation
● Goal
– Method to use
– Recommender system to use for comparison
● Method
– Systematic review
– 69 papers included
● Result
– User studies most used

24. 24
Semantic Annotator
Text
Processor
Semantic
Broker Resolvers
Semantic
Filter
Aggragator

25. 25
UGC Manager
REST
API
SPARQL
Endpoint
SQL
RDF