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Smart Subjects: Application Independent Subject Recommendations

Smart Subjects: Application Independent Subject Recommendations. Tito Sierra NCSU Libraries Code4Lib 2007. Outline. Concept Motivation Smart Subjects Applications How it Works Strengths and Weakness Future Plans. Smart Subjects Concept. Input: User search query Output:

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Smart Subjects: Application Independent Subject Recommendations

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  1. Smart Subjects: Application Independent Subject Recommendations Tito SierraNCSU LibrariesCode4Lib 2007

  2. Outline • Concept • Motivation • Smart Subjects Applications • How it Works • Strengths and Weakness • Future Plans

  3. Smart Subjects Concept Input: • User search query Output: • A list of related library subjects

  4. Smart Subjects Concept Input: • User search query Output: • A list of related library subjects Basically a subject recommendation engine.

  5. Input: music therapy Output: Music Curriculum & Instruction Education Communication & Media Psychology Biochemistry Example 1

  6. Input: asymptotic stability Output: Bioinformatics & Biomathematics Statistics Mathematics, Science & Technology Education Mathematics Computer Science Aerospace Engineering Example 2

  7. Input: illegal immigration Output: Criminology Political Science Public Administration Biology Zoology Industrial Engineering Example 3

  8. Input: illegal immigration Output: Criminology Political Science Public Administration Biology Zoology? Industrial Engineering Example 3

  9. Search log analysis: standard, international economic development, fines, dissertation abstracts, music therapy, ACM, wolfcopy, Oxford English Dictionary, audio, illegal immigration, schedule, interlibrary, datamonitor, chemistry, JAMA, CRC, photography, vision, wiley, ciation builder, job, academic search elite, ria, film studies, career development, sanborn maps, citation index, iee, history, industry analysis, scholarly journals, ethics, spss, petition, animal behavior, psych info, repository, ENR, diabetes, data, lrl, cancer, textbooks, wharton, Christian Science Monitor, ITTC, blah, PubMed, time magazine, nutrition, DVD, questia, conductive heat transfer, sage, newspaper Motivation

  10. Search log analysis: Lots of topical subject queries in the long tail! standard, international economic development, fines, dissertation abstracts, music therapy, ACM, wolfcopy, Oxford English Dictionary, audio, illegal immigration, schedule, interlibrary, datamonitor, chemistry, JAMA, CRC, photography, vision, wiley, ciation builder, job, academic search elite, ria, film studies, career development, sanborn maps, citation index, iee, history, industry analysis, scholarly journals, ethics, spss, petition, animal behavior, psych info, repository, ENR, diabetes, data, lrl, cancer, textbooks, wharton, Christian Science Monitor, ITTC, blah, PubMed, time magazine, nutrition, DVD, questia, conductive heat transfer, sage, newspaper Motivation

  11. Motivation Existing work: • Subject Browse portal at NCSU

  12. Subject Browse at NCSU • Locally developed subject classification launched in Fall 2005 • 100 subject nodes in 12 top-level categories • Subject nodes influenced by the university curriculum (e.g. Crop Science)

  13. Subject Browse at NCSU

  14. Subject Browse at NCSU

  15. Smart Subjects Applications • Quick Search integration • OpenSearch interface

  16. Quick Search Integration

  17. Quick Search Integration

  18. Quick Search Integration

  19. OpenSearch Interface

  20. OpenSearch Interface

  21. How it Works • Harvest available institutional data • Course catalog descriptions • Faculty publications citations • Create “text extract” representations for each academic department on campus • Index the text extracts • Retrieval interface queries indices • Retrieval algorithm crosswalks academic departments to library subject classification

  22. How it Works

  23. How it Works

  24. How it Works

  25. Technology Used • SWISH-E for indexing • PHP for retrieval processing/scoring

  26. Strengths • Application and collection independent • Subject recommendations can be integrated in any library search application • Encourages broader, serendipitous resource discovery

  27. Weaknesses • False positives (bad recommendations) • Zero hits (no recommendations)

  28. Future Plans • Deploy new uses of Smart Subjects tool • Database Advisor • Increase the size of subject indices • Article table of contents data • Backlog of course descriptions • Gauge interest for a community subject recommendation platform

  29. More Information Project Site: http://www.lib.ncsu.edu/dli/projects/smartsubjects

  30. Thanks! Tito Sierra NCSU Libraries tito_sierra@ncsu.edu

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