Knowledge organization on the Web ISKO-IWA meeting
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1 Knowledge organization on the Web ISKO-IWA meeting
2 German Social Science Infrastructure Services Digital Library Data archive Consulting Surveys & studies Society observation
3 German Social Science Infrastructure Services Document types: Bibliographic Full texts Project data Institutions Web pages Statistical data Surveys People Disciplines: Sociology Political Science Education Psychology Economics Business Administration
4 Heterogeneous collections Many databases: document types / formats vocabularies controlled vocabularies: internal consistency intersystem compatibility (semantic heterogeneity) Solution: translate cross-walks terminology mapping
5 KoMoHe Project September Goals: Models for searching heterogeneous collections Development, organization & management of cross-walks between controlled vocabularies
6 Terminology Mapping Initiatives OCLC Terminology Services DDC, LCC, LCSH, Mesh MACS (Multilingual Access to Subjects) LCSH Rameau SWD CARMEN SWD, TheSoz, STW, Criss-Cross SWD DDC
7 Cross-concordances = manually created, directed relations between controlled terms of two knowledge organization systems (KOS) KOS 1 100% KOS 2 50% mapped KOS 1 Computer KOS 2 Information System KOS 3 40% KOS 4 60% mapped KOS 2 Information System KOS 1 Database
8 Relations Equivalence KOS 1 Relation KOS 2 Narrower Term Broader Term Library Library = > Bibliothéque Special library Related Term Null: no mapping Thesaurus Hacker Virus < ^ 0 KOS Computers + Security
9 Cross-concordances 25 Vocabularies in 60 cross-concordances Thesauri (16) Descriptor lists (4) Classifications (3) Subject heading lists (2) 380,000 mapped terms 465,000 relations 205,000 equivalence relations 13 German, 8 English, 1 Russian, 3 multilingual
10 Disciplines Agricultural science (1) Information science (1) Gerontology (1) Medicine (1) Universal (3) Social Sciences (10) Political science (3) Economics (2) Pedagogics (1) Sports science (2) Psychology (1)
11 Differences Vocabulary type: Thesaurus Thesaurus Classification Thesaurus (Classification Classification) (Thesaurus Descriptor list) Change of discipline Change of language Size Combination / compounds
12 Thesaurus Thesaurus Related Term 14% Null Mapping 12% Identical equivalence 21% Narrower Term 9% Broader Term 20% Equivalence (Synonym) 24%
13 Classification Thesaurus (JEL STW) Related Equivalence Term 6% 8% Broader Term 11% Narrower Term 75%
14 Information Retrieval Tests GOAL: Facilitate search across different databases Navigate without semantic borders! Translate search terms into other terminologies Increase diversity of documents Improve search experience without effort for searcher
15 Information Retrieval Tests 1. Do mappings improve subject search? CT (start vocabulary) TT Destination database 2. Do mappings improve free-text search? FT (start vocabulary) FT + TT Destination database
16 Information Retrieval Tests Thesaurus mapping only Only equivalence relations Real queries (~6 per tested cross-concordance) Databases: 80, mio. documents Test 1 (CT TT): 13 Cross-concordances Test 2 (FT FT+TT): 8 Cross-concordances
17 Information Retrieval Tests - Results CT TT (Improvements in %) Intradisciplinary Interdisciplinary Recall = Hitrate +39% +136% Precision = Accuracy +34% +68% FT FT+TT (Improvements in %) Intradisciplinary Interdisciplinary Recall = Hitrate +20% +24% Precision = Accuracy -12% -24%
18 Sowiport Portal:
19 Sowiport Thesaurus
20 Sowiport Search
21 Conclusion Cross-concordances improve subject search with controlled terms & free-text search Only 24% relations utilized (equivalence) Potential: Other relations Natural language query terms CT translation More mappings which are not evaluated Sowiport:
22 Publications Mayr, Philipp; Petras, Vivien (2008): Cross-concordances: terminology mapping and its effectiveness for information retrieval. In: 74th IFLA World Library and Information Congress. Québec, Canadahttp:// Mayr, Philipp; Mutschke, Peter; Petras, Vivien (2008): Reducing semantic complexity in distributed Digital Libraries: treatment of term vagueness and document re-ranking. In: Library Review. 57 (2008) 3. pp Mayr, Philipp; Petras, Vivien (2008 to appear): Building a terminology network for search: the KoMoHe project. In: International Conference on Dublin Core and Metadata Applications.
23 Databases without semantic borders
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