Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs
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Transcript of Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs
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October 24, 2009 Using Ontologies To Strenghten Folksonomies and Enrich Information Retrieval in Weblogs - ICWSM 2007 1
Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs
Alexandre Passant EDF, Recherche & Développement, Clamart, France Université Paris 4, Laboratoire LaLICC, Paris, France
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1 Corporate Blogging
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Classical (old-school) information systems
• Features: • Workflows • Access Control • Templates • Archives
• Designed to store: • Project reports • Internal notes • Hierarchical information
• But, what about informal and unstructured content: • Short news • E-mails • Coffee-break discussions
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A new vision: Enterprise 2.0
• Web 2.0 concepts in a corporate environment
• Write and share any knowledge:
• Blogs • Comments, trackbacks
• Re-use and capitalize knowledge:
• Wikis • Open structure and cooperation
• Be informed:
• RSS feeds • Shared subscriptions
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EDF R&D Experiment
• EDF R&D: • 2000 researchers • 3 research centers
• Our platform: • RSS subscription system • Blogs • Group wikis
• Experiment (1 1/2 year): • 1500 feeds, 8000 blog posts • 80 bloggers, 600 readers / subscribers
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2 Weblogs Indexing and Folksonomies
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Indexing blog posts
• Meta-data about the container:
• Automatically-created metadata: • Author, creation date, title
• DublinCore standards • Meta-data about blog post content:
• Previously-defined: • Ontologies, taxonomies
• User-defined: • Free keywords and folksonomies
• Folksonomies: • Easy to adopt • Build from scratch
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Folksonomies limits
• Tags variation: • Different tags for the same meaning:
• Synonymy, Abbreviation, Acronyms … • Typos
• Tag ambiguity: • Different meanings for the same tag:
• Acronyms, Homonymy …
• Flat organisation: • No way to suggest related tags
• Paris / France • blog / socialsoftware
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Ambiguity example from del.icio.us
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Some tools to reduce variation and explosion
• Tag completion: • Forward and “backward” completion • AJAX
• Tag suggestion: • Based on blog post content • Suggesting existing tags • But also new ones using named entites extraction • AJAX
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3 The Semantic Web
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A Few Words About the Semantic Web
• Semantic Web
• Extending the current Web • Unified description of resources
• Ontologies
• Representation of a domain • Common vocabulary
• Languages
• Modeling: RDF(S), OWL … • Querying: SPARQL …
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Weblogging and the Semantic Web
• Tools: • Snippet Manager [Cayzer & al. 2005] • semiBlog [Möller & al. 2006]
• Folksonomies: • Tag ontology to represent connections between tags [Newman 2005] • Tagging model [Gruber 2005]
• Vocabularies:
• RSS 1.0 based on RDF, can be extended with other vocabularies • SIOC: Semantically-Interlinked Online Communities [Breslin & al. 2005]
• State of The Art: • « What next for Semantic Blogging » [Cayzer 2006]
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4 Strengthening Folksonomies
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A mix of Folksonomies and Ontologies
• Mixing both approaches • Keep the open spirit of folksonomies • Use an ontology layer as a formal way to represent data • Remove ambiguity and add meaning to tags to enhance search experience
• How ? • Link tags to domain ontology concepts (classes / instances) • Create links between posts and ontology concepts using SIOC
• First steps • Analyse the folksonomy and most popular tags • Create a core ontology (based on PROTON) and its instances • 300 classes, 600 instances, mainly named entities
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A simple way to link tags to ontology instances
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From Tags to Ontology (1/5)
1) Create and tag post
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From Tags to Ontology (2/5)
1) Create and tag post
2) Link tag to ontology
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From Tags to Ontology (3/5)
1) Create and tag post
2) Link tag to ontology
3) Link post to ontology
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From Tags to Ontology (4/5)
1) Create and tag post
2) Link tag to ontology
3) Link post to ontology
4) Create new post
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From Tags to Ontology (5/5)
1) Create and tag post
2) Link tag to ontology
3) Link post to ontology
4) Create new post
5) Infer related post
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Dealing with ambiguity and maintaining instances
• User interface to remove ambiguity when adding a new post
• Ability to browse the ontology to link to other class / instance for new / different meaning tags
• Restricted back office to create new instances
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5 Enhanced Information Retrieval
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A Semantic Search Engine
• Decentralized data:
• Ontologies • Blog posts w/ RDF description • A central 3store w/ SPARQL
• Using tags / ontology links to:
• Deal with tags variations • Remove ambiguity
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Suggesting related tags and posts
• Goal:
• Offer suggestions to users based on their current tag search • Let users discover potential interesting posts • Different approaches, use both tagging and ontologies:
• Using instances co-occurrence • Using instances type • Defining specific rules
• Run on the fly and suggest results, using SPARQL
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Using instances co-occurrence
• Basic approach:
– Posts sharing concepts
– Ontology to remove ambiguity
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Using instances types
• Suggesting instances of the same class:
– Programming languages
– Energy companies
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Defining specific rules
• Rule(s) for each class
• Location / {sub|top}locations • Company / companies working
in the same area
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Rule example
• RDF rule {! :x rdf:type sioc:post .! :y rdf:type sioc:post .! :x sioc:topic :a .! :y sioc:topic :b .! :a rdf:type ptop:Agent .! :b rdf:type ptop:Agent .! :a company:expertiseIn :d .! :b company:expertiseIn :d !} => {! :x sioc:related_to :y !} .
• Reformulated w/ SPARQL SELECT ?post ?topic ?domain!WHERE {! <$uri> [! rdf:type ptop:Agent ;! company:expertiseIn ?domain! ] .! ?post sioc:topic ?topic .! ?topic [! rdf:type ptop:Agent ;! company:expertiseIn ?domain! ] !}
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Running and Displaying results
• SPARQL queries on the triplestore
• Offering different tagclouds to split results in clusters:
• Instances • Specific rules • Co-occurrence
• Let users know why they should have a look to related posts
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6 Conclusion
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Conclusion
• Mixing folksonomies and ontologies • Keep simplicity of free tagging • Ontologies to reduce limits of free tagging • Infer related posts / topics • A mix of top-down and bottom-up approach
• A real use-case • Adapt model and interfaces to users needs
• Future works • Knowledge extraction from weblogs • Use wikis to add properties to ontology instances • New ways to browse and query blog posts
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Thank you !