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Vocabulary Matching for Book Indexing Suggestion in Linked Libraries – A Prototype Implementation & Evaluation

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Vocabulary Matching for Book Indexing Suggestion in Linked Libraries – A Prototype Implementation & Evaluation. Antoine Isaac , Dirk Kramer, Lourens van der Meij, Shenghui Wang, Stefan Schlobach, Johan Stapel. Problem: subject indexing. Describing subjects of books

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slide1

Vocabulary Matching for Book IndexingSuggestion in Linked Libraries – A PrototypeImplementation & Evaluation

Antoine Isaac, Dirk Kramer, Lourens van der Meij, Shenghui Wang, Stefan Schlobach, Johan Stapel

problem subject indexing
Problem: subject indexing
  • Describing subjects of books
  • Using concepts from vocabularies (e.g. thesauri)
problem re indexing
Problem: re-indexing
  • Describing a book that has already be described
  • With a new vocabulary
    • Fitting a different context (e.g., different libraries)
why re indexing at kb
Why re-indexing at KB?
  • The Dutch National Library (KB) holds many books that are also in other Dutch public libraries
  • KB deposit uses Brinkman thesaurus for indexing
  • Public Libraries use Biblion thesaurus
a wider issue
A wider issue
  • KB shares books with many other libraries
  • All having their own description practices
room for improvement
Room for improvement?
  • Libraries devote large resources to indexing
    • 20 people at KB
    • About 20,000 books per year
  • Leveraging already existing descriptions for re-indexing can be beneficial for both sides
alignment and re indexing
Alignment and re-indexing
  • STITCH project
    • Tackling semantic interoperability in Cultural Heritage
    • Using ontology alignment
  • Mappings between concepts from different vocabularies can be used for re-indexing

Basic idea: replace concepts in descriptions

by conceptually equivalent concepts

goal a re indexing prototype
Goal: a re-indexing prototype
  • Past: preliminary experiments with KB data
  • Now: building a prototype and
    • plugging it onto the KB production system
    • having it evaluated by its potential users (indexers)
  • Prototype case: Dutch public libraries / KB

Suggesting Brinkman subjects based on Biblion ones

alignment and re indexing requirements
Alignment and re-indexing: requirements

Subjects can be complex

  • Mappings between groups of concepts

"Travel guides" + "Spain" → "Spain; travel guides"

Concepts are used in descriptions

  • Mappings taking into account extensional semantics

"Building engineering"

→ "Learning material ; building engineering"

obtaining re indexing rules
Obtaining re-indexing rules
  • Lexical alignments are not good enough
  • Probabilistic rules are calculated
    • Using extension of concepts: existing indexing
    • Simple probabilities, with adhoc adjustment

"Travel guides","Spain"→"Spain; travel guides", 0.982

  • Not only based on Biblion subjects
    • AUT – main authors of books
    • KAR – “characteristic”
    • DGP – intellectual level/target group
slide11
Demo

Doesn\'t work?

user study
User study
  • Quantitative aspect
    • How well does the tool compare to human subject indexing?
  • Qualitative aspect
    • User satisfaction
    • Improvement suggestion
evaluation setting
Evaluation setting
  • 6 indexers
  • 6 weeks
  • 284 books
  • Evaluation integrated in daily indexing work
  • Pre-evaluation briefing
  • Questionnaire during evaluation
  • Post-evaluation de-briefing & questionnaire
user study results
User study results
  • Top ranked mappings are indeed much better
  • Individual book satisfaction level > 70%
user study results 1
User study results (1)
  • But the general satisfaction is lower
    • Only two out of six would use the tool as such
  • Quality of suggestions
    • Lower-level suggestions are often not meaningful
  • Perception of suggestions\' quality
    • Long lists with wrong suggestions ad the end are bad
    • Ranking is appreciated, but it is not enough
user study results 2
User study results (2)

Suggestions were found promising

  • Bridging the indexing gap between collections
    • Different indexing strategies

"Persian language" (Biblion)

vs. "Iranian language and literature" (Brinkman)

Lots of suggestions for improvement

  • More re-indexing!
    • Suggesting concepts from other vocabularies
    • More context metadata as input
conclusions
Conclusions
  • Shows the potential of re-using data in a library network
  • Alignment approach fitting indexing practice
  • Concrete demonstration, in KB production environment
  • Technology transfer: KB wants to continue efforts
  • Flexibility: architecture ready to exploit other vocabularies
    • Linked data & SKOS
thank you
Thank you!
  • Questions?
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