Controlled%20Vocabularies%20in%20TELPlus

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Controlled Vocabularies in TELPlus

• Antoine ISAAC
• Vrije Universiteit Amsterdam
• EDLProject Workshop
• 22-23 November 2007

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Agenda

• TELPlus Context
• Improving subject access
• 3 sub-tasks
• Services for TEL

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TELPlus Context

• Started October 2007
• Running 27 months
• Content WPs
• OCRing previously digitised material
• Improving the usability of TEL through OAI PMH
  compliancy
• Improving Access
• Integrating services with TEL portal
• User personalisation services
• Extending TEL to Bulgaria Romania

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WP3 Improving Access

• Task 1 Indexing for usability
• Review/test state-of-the-art semantic search
  engines
• On content of documents
• Task 2 Improving subject access
• Task 3 FRBR aggregation, search and browsing
• Create/exploit FRBR metadata repositories
• Task 4 Focus on users
• Focus groups on prototypes

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WP 3 Task 2 Improving Subject Access

• Improving subject access via semantic alignment
  between subjects
• Search through collections
• Using metadata
• In a controlled setting
• Paving the way for enhanced usages
• Advanced treatments mentioned in TELplus need
  conceptual structures and links between these
  structures
• E.g. clustering

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WP 3 Task 2 Improving Subject Access

• Improving subject access via semantic alignment
  between subjects
• Reference MACS project
• Manually-built semantic equivalences between
  Rameau, SWD LCSH headings

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MACS Querying Collections
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MACS Query Reformulation Options
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WP 3 Task 2 Improving Subject Access

• Improving subject access via semantic alignment
  between subjects
• Reference MACS project
• Manual equivalences between Rameau, SWD, LCSH
  headings
• Here an experiment on deploying automatic
  alignment techniques
• Determining possible strategies
• Assessing feasibility and usefulness
• MACS context

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WP3.2 Sub-tasks

• 3.2.1. Converting the subjects to standard
  representation language
• Semantic web format (SKOS)
• 3.2.2. Aligning the vocabularies
• Semantic correspondences between subjects
• 3.2.3. Deploying the alignment knowledge obtained
  into TEL framework
• E.g. using links to reformulate queries from one
  subject list to the other

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Converting subjects to standard representation
language

• Goal solving syntactic heterogeneity between
  vocabularies
• Enabling the use of standard tools
• E.g. for query (re)formulation
• Paving the way for dealing with semantic
  heterogeneity
• Definitions of concepts expressed according to a
  common model

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Converting subjects to standard representation
language

• Approach Semantic Web and SKOS
• Semantic Web
• Knowledge objects as web resources (URIs)
• Description by linking resources (RDF)
• Description using shared formal vocabularies
  (ontologies)
• SKOS
• A standard Semantic Web model (ontology)
• For knowledge organization systems (thesauri,
  subject heading lists)

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SKOS Example
skosConceptScheme
rdftype
skosConcept
http//www.iconclass.nl/
rdftype
skosinScheme
http//www.iconclass.nl/s_11F
skosprefLabel
skosbroader
the Virgin Mary_at_en
la Vierge Marie_at_fr
skosprefLabel
http//www.iconclass.nl/s_11
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Converting subjects to standard representation
language - Process

• Getting processable versions from owners
• E.g. XML
• Analyzing the models
• Converting to SKOS

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WP3.2 Sub-tasks

• 3.2.1. Converting the subjects to standard
  representation language
• Semantic web format (SKOS)
• 3.2.2. Aligning the vocabularies
• Semantic correspondences between subjects
• 3.2.3. Deploying the alignment knowledge obtained
  into TEL framework
• E.g. using links to reformulate queries from one
  subject list to the other

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Vocabulary Alignment

• Specifying required alignment format (links)
• Type of mapping links equivalence, broader
• Cardinality one-to-one, one-to-many
• Taking application context (TEL) into account

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Vocabulary Alignment

• Specifying required alignment format (links)
• Selecting ( running) alignment techniques/tools
• Inspired by semantic web approaches

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Vocabulary Alignment Techniques

• Similar to ontology alignment problem
• Existing approaches for (semi-) automatic
  ontology alignment
• Using techniques from linguistics, computer
  science, statistics
• Problem performances do not allow 100 automatic
  alignment
• Problem multilingual case
• Some techniques cannot be used

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Potential Technique Using Background Knowledge

• Using a shared conceptual reference to find links

Publication
Calendar
SHL 1
SHL 2
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Potential Technique Statistical Alignment

• Object information (book indexing)

Dutch Literature
SHL 1
SHL 2
Dutch
Dually-indexed books
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Vocabulary Alignment

• Specifying required alignment format (links)
• Selection ( running) of tool/method
• Evaluation ( cleaning)
• Considering application

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Evaluation of Alignments

• MACS has produced mappings!
• Possible gold standard
• But has MACS produced all mappings?
• Which proportion of the SHLs is covered?
• Taking into account all indexing strings?
• Are MACS mappings the only interesting ones?
• Serendipity mappings
• Concepts that are not equivalent but could bring
  useful results when added to queries
• Compensating for indexing variability

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Evaluation of Alignments

• Several scenarios for using and evaluating
  alignments
• Concept-based search
• Re-indexing
• Integration of one SHL into the other
• SHL Merging
• Free-text search
• Navigation

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Evaluation of Alignments

• Several scenarios for using and evaluating
  alignments
• Concept-based search
• Retrieving books indexed by SHL1 using SHL2
  concepts
• Re-indexing
• Integration of one SHL into the other
• SHL Merging
• Free-text search
• Matching user search terms to both SHL1 or SHL2
  concepts
• Navigation
• Browsing several collections using one SHL
  structure

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Evaluation of Alignments

• Several settings for a single scenario
• Fully automatic reformulation vs assisted
  reformulation (candidates)
• Different evaluation measures
• Good mappings vs acceptable ones
• Number of candidates for reformulation
• Semantic closeness to original query

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Vocabulary Alignment

• Specifying required alignment format (links)
• Selection ( running) of tool/method
• Evaluation ( cleaning)
• Assessment of the approach
• Efforts required, quality, extendibility

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WP3.2 Sub-tasks

• 3.2.1. Converting the subjects to standard
  representation language
• Semantic web format (SKOS)
• 3.2.2. Aligning the vocabularies
• Semantic correspondences between subjects
• 3.2.3. Deploying the alignment knowledge obtained
  into TEL framework
• E.g. using links to reformulate queries from one
  subject list to the other

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Deploying the alignment knowledge obtained into
TEL framework

• Observing integration of MACS data into TEL
• Conceptual input for alignment requirements
• Integration of the obtained alignment in TEL
• Assessment of the alignment integration
• Technical aspects, usage aspects

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Reminder

• Alignment is a difficult problem
• Application-specific alignment pretty much
  unexplored in Semantic Web research
• More a feasibility study than a complete solution
  to the problem
• Practical goal investigate how automatic
  techniques could help MACS-like initiatives
• Manual mapping is labour-intensive

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Agenda

• TELPlus Context
• Improving subject access
• 3 sub-tasks
• Services for TEL

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WP4 Integrating services with the European
Library portal

• Theo van Veen (KB)
• Tasks
• Identifying services that are going to give the
  user the greatest return
• Creating new services
• Integrating services within TEL

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WP4 Some Services Mentioned

• Preliminary inventory no official commitment!
• Services based on controlled vocabularies
• Thesaurus and name authority service
• Providing terms linked to query terms
• Semantic enrichment service
• Users can annotate search results with terms
• Distance between terms and related terms

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WP4 Some Services Mentioned

• Preliminary inventory no official commitment!
• Services based on controlled vocabularies
• Thesaurus and name authority service
• Semantic enrichment service
• Distance between terms and related terms
• Adding more value from controlled vocabularies
  and alignments between them

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Thanks!