1. Taxonomies, Lexicons and Organizing Knowledge
Wendi Pohs, IBM Software Group,
Infotoday 2003 Content Management Symposium
May 8, 2003
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2. Agenda Benefits, business and technical Definitions
Planning and Implementation
Issues
Futures
Q&A
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3. The Mantra
Knowledge is in the eye of the beholder, but reflecting end user needs is as critical as representing texts....and it takes work!
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4. Business Benefits - Lifecycle Integration
eLearning
Technology, Government, Pharmaceutical
Regulatory Compliance
Pharmaceutical, Government
Corporate accountability
Financial, Life Sciences
Intellectual Capital Management
Consulting, Law firms, Financial
Innovation, Discovery
Government, Pharmaceutical, Retail, Technology
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5. Technical Benefits Integration with content management systems
Site creation
Site navigation
Enhance full text search
Gap analysis
Personalization
Defining skills, areas of expertise
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6. Definitions: Taxonomy
“The science, laws or principles of classification” (From the Greek: rules of arrangement)
Biology (Linnaeus)
Education (Bloom)
A hierarchical collection of categories and documents
Structure and content
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7. Definitions: Lexicon A word book or dictionary
Vocabulary of a particular field of study
Keywords, synonyms, jargon
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8. Definitions: Directory
More general than taxonomy
Natural structure
Wide vs deep
Category structure less controlled
File system
Yahoo (
Yellow Pages
Corporate Web sites (
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9. Definitions: Thesaurus
Controlled vocabulary
Subject headings, labels
Synonyms (U, UF)
Relation types (TT, BT, NT,SN, HN, RT, SA)
Examples:
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10. Definitions: Meta-data and Tags
Properties, attributes: information describing types of data [Crandall]
The ‘energy’ required to keep things organized [Earley]
Tags
<META>, <Source>
Document Properties
$CreatedBy
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11. Definitions: Classification
Analyzing documents and assigning them to predefined categories
Rule-based vs natural
Statistical vs semantic
Classification schemes
Dewey
Library of Congress
Industry-specific
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12. Planning: Initial Analysis
Determine user needs thru content, knowledge audits
What is the objective of the system?
What are typical "day in the life" scenarios?
Do you need to comply with existing standards?
Select representative content
No need to include every document in every source
Look for a subset of documents with
Good meta-data (Titles, Authors)
Rich, representative body text
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13. Implementation: Creation and strategy
Create an initial taxonomy
On paper, on a whiteboard, in a spreadsheet
Look at existing databases, Web sites, org charts
Reuse good, representative categories
Prototype taxo structure (flat, hierarchy, associative)
Review the initial taxonomy
Determine a categorization strategy
Rules-based, keyword-based, statistical, others
Review taxonomy creation, content management tools
Consider resource requirements for taxonomy maintenance
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14. Implementation: Testing and Maintenance
Test the taxonomy
Track queries to determine accuracy
Enable categorization to test strategies; refine if necessary
Test with disparate user groups
Maintain taxonomy
Establish a workable change-management process
Move documents, promote/demote categories, merge/delete as necessary
Add more content
Iterate
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15. Issues: Understand the BIG issues
Maintenance
Content expert or info professional
Multiple taxonomies
Organizational “perfection complex” [Chait]
Categorization strategy
Manual, automatic, both
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16. Issues: Multiple taxonomies
Many editors
Term approval process, synonyms
Standard tools across the enterprise
Federated taxonomies
Taxonomy links, “cross-connections,” facets, views
Taxonomy mapping
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17. Futures
Methods:
Feature extraction, statistical analysis, rules-based, better semantics, label generation
Starter taxonomies, imports
"Plug and play" classifiers
Taxonomy mapping
Interfaces: Visualization, better training tools
Semantic Web
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19. Q&A
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