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Museum Recommender

     Mara Dumitru
Museum Visits while Traveling
               • Choose National
                 Museum:
                 – General overview
                 – Many different painters
                   and styles
                 – Overlook favorite artists
                   or artistic period
Purpose
• For art lovers
• Recommend museums in the users’ city based on their
  preferred artist and artistic period
• Two types of recommendations:
  – The best recommendation finds museums that contain both
    the given artist’s work and the works of artists belonging to the
    preferred artistic period
  – The second best recommendation finds museums that only
    contain works of either one of the two preferences
Method
• 3 user inputs as strings which are transformed
  into URIs
  – current city
  – favorite artist
  – favorite artistic period
• Include the strings in the queries for DBpedia
• Generate URIs of museums, based on input (i.e.
  user preferences)
Ontology
Implementation
• 2 SPARQL queries which select museums:
  – Intersect artist and period
  – Union to include results from either one
• Implemented in Java (Jena library)
• Prints to file a set of RDF triples, describing
  the recommendation and its type, using the
  URIs and the ontology
Demo
Advantages
• Even if the period the artist belongs to does
  not match the preferred period…
           Favorite artist: Jan van Eyck
           (Period: Renaissance)




                    Favorite period: Impressionism
Demo
Drawbacks (DBpedia)
• Missing information
• Limits the number of links
  between artists, periods and
  museums
• Not enough properties, such
  as painting theme
Semantic Web
• Enables the implementation of recommendation
  programs that analyze and select suggestions,
  based on a user profile.
• Web interaction becomes more personalized and
  more precise, with the increasing number of
  databases and querying methods.
• Museum Recommender: simple preferences are
  retrieved in DBpedia and connected to each
  other, resulting in suggestions which are only
  suitable for the user.
Semantic Web
• Uses SPARQL to query for museums in
  DBpedia.
• Includes recommendation types as OWL
  individuals, in order to better define the RDF
  triples.
Future Implementations
• Museum Recommender as a mobile
  application
  – especially practical for short travels
  – generates museums that contain user’s preferred
    artists and periods
  – recommends museums in a fast and personalized
    manner, anywhere in the world
How to Improve
• Find cities near the user’s given
  location that represent similar or
  better recommendations for
  museums.
• Add the theme (landscape,
  portrait, historical painting, etc.)
  as one of the user’s inputs and
  include this preference in the
  recommendation.

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Museum Recommender using Semantic Web

  • 1. Museum Recommender Mara Dumitru
  • 2. Museum Visits while Traveling • Choose National Museum: – General overview – Many different painters and styles – Overlook favorite artists or artistic period
  • 3. Purpose • For art lovers • Recommend museums in the users’ city based on their preferred artist and artistic period • Two types of recommendations: – The best recommendation finds museums that contain both the given artist’s work and the works of artists belonging to the preferred artistic period – The second best recommendation finds museums that only contain works of either one of the two preferences
  • 4. Method • 3 user inputs as strings which are transformed into URIs – current city – favorite artist – favorite artistic period • Include the strings in the queries for DBpedia • Generate URIs of museums, based on input (i.e. user preferences)
  • 6. Implementation • 2 SPARQL queries which select museums: – Intersect artist and period – Union to include results from either one • Implemented in Java (Jena library) • Prints to file a set of RDF triples, describing the recommendation and its type, using the URIs and the ontology
  • 8. Advantages • Even if the period the artist belongs to does not match the preferred period… Favorite artist: Jan van Eyck (Period: Renaissance) Favorite period: Impressionism
  • 10. Drawbacks (DBpedia) • Missing information • Limits the number of links between artists, periods and museums • Not enough properties, such as painting theme
  • 11. Semantic Web • Enables the implementation of recommendation programs that analyze and select suggestions, based on a user profile. • Web interaction becomes more personalized and more precise, with the increasing number of databases and querying methods. • Museum Recommender: simple preferences are retrieved in DBpedia and connected to each other, resulting in suggestions which are only suitable for the user.
  • 12. Semantic Web • Uses SPARQL to query for museums in DBpedia. • Includes recommendation types as OWL individuals, in order to better define the RDF triples.
  • 13. Future Implementations • Museum Recommender as a mobile application – especially practical for short travels – generates museums that contain user’s preferred artists and periods – recommends museums in a fast and personalized manner, anywhere in the world
  • 14. How to Improve • Find cities near the user’s given location that represent similar or better recommendations for museums. • Add the theme (landscape, portrait, historical painting, etc.) as one of the user’s inputs and include this preference in the recommendation.