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KB subject prediction tool

KB subject prediction tool. KB subject prediction prototype Introduction. Subject prediction is a special case of book reindexing What is reindexing? Why build a subject prediction tool? How does subject prediction work? The technical aspects of the tool DEMO User study results.

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KB subject prediction tool

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  1. KB subject prediction tool

  2. STITCH final event KB subject prediction prototype Introduction • Subject prediction is a special case of book reindexing • What is reindexing? • Why build a subject prediction tool? • How does subject prediction work? • The technical aspects of the tool • DEMO • User study results

  3. STITCH final event What do we mean by re-indexing? • 2 collections • Each described (indexed) by its own thesaurus/classification system

  4. STITCH final event The re-indexing application • Goal: have the book of one collection described by the thesaurus used in the second collection • For instance: if one thesaurus is dropped, old books have to be indexed according to the other thesaurus

  5. STITCH final event Book re-indexing • Goal: converting source indexing to a target indexing system • From original thesaurus • To new thesaurus

  6. STITCH final event KB subject prediction prototype • Book reindexing as a possiblyvaluable tool for the KB • Reindexing as a usage scenario for vocabulary alignment • Deployment of alignment techniques into a real world context • Scenario-specific, vocabulary alignment • Introduction of SW techniques into KB practice

  7. STITCH final event KB subject prediction prototype Prototype: • NBD/Biblion (LTR) to Brinkman • Books already indexed by Public libraries • Integration into WinIBW software • the access tool to the Pica Library system used at KB • User Study • tool evaluated by 6 experienced indexers (titelbeschrijvers)

  8. STITCH final event How to predict Brinkman Subjects? • Given NDB/Biblion subject metadata values, predict Brinkman • Used 240000 common books • Tried different reindexing strategies • Used standard (lexical and instance based) techniques • Developed an alignment using statistical techniques. Very specific to scenario, using more metadata • LTR -- Biblion concepts, • AUT -- main authors of books, • KAR -- ``characteristic'' and • DGP -- intellectual level/target group.

  9. STITCH final event Subject Suggestion Rules

  10. STITCH final event KB re-indexing prototype

  11. STITCH final event Book indexing suggestion tool

  12. STITCH final event User Study • 6 indexers (titelbeschrijvers) of the “Depot collectie”. • They used the tool for 6 weeks • only if a book contained LTR → 284 books. • Marked the suggestions, • Filled in two questionnaires • Gave verbal feedback in final meeting

  13. STITCH final event Most important results for user satisfaction • Technically the tool was ok, but the robustness (storingsgevoeligheid) absolutely needed to be improved. • Users were interested in the tool and would keep on using it provided its quality is improved. Most important directions for improvement: • More robust • More often applicable • Better subject suggestions

  14. STITCH final event Results User Study: quality of suggestions • Which suggestions were chosen among the ones presented to the indexer? • precision: percentage of suggestions that were correct • recall: percentage of the subjects chosen by indexers that were found by the tool.

  15. STITCH final event Thanks evaluators! Bedankt Margot, Donita, Bernadette, Judith, Rob, Arjan

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