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Building taxonomies from the ground-up. Prakash Govindarajulu Managing Consultant RealTech Inc prakashgovind@realtechinc.com 781-883-8338. Taxonomy and Semantics. Why taxonomies? How can they influence semantics? Bottom-up methodology for building them. Taxonomy. Search. Semantic
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Building taxonomies from the ground-up Prakash Govindarajulu Managing Consultant RealTech Inc prakashgovind@realtechinc.com 781-883-8338
Taxonomy and Semantics • Why taxonomies? • How can they influence semantics? • Bottom-up methodology for building them Taxonomy Search Semantic System
P2P Communication – inherent semantics • Richness of Dialog, opportunity to: • Clarify context - Clarify query - Refine query - Answer if known
The Semantic Problem Information Systems The semantic problem: - Knowledge representation - Capturing domain expertise - Accessing knowledge without loss of richness of dialog
Terminology:data, information, knowledge Knowledge • Data: any fact • Metadata/Information:the act or fact of informing. • Data about data • Provides context • Relationship with other data objects • Knowledge:the fact or state of knowing; the perception of fact or truth • Interpreted data, “understands” data and information to refine or fulfil a query • Experiential data Metadata Data
“Knowledge” Representation Today Systems With Data (documents, Database Wikis blogs) Information Access Systems (Search)
Search – Yet Another Index? Systems With Data (documents, database) Information Access Systems (Search) Index
Challenges Systems With Data (documents, database) Information Access Systems (Search) Index • User’s perspective is not well understood • Search relevancy therefore suffers • How can related information be presented? • Solution approach: Taxonomy
Taxonomy anyone? From digg.com 6/8/07
Taxonomy – Classification Classification: Categories & Subcategories
Taxonomy – Guided Navigation Perspectives or Facets
Building Taxonomy – the Human Element Systems With Data (documents, database) System With Metadata (Taxonomy) Information Access Systems (Search) Human Element Consensus Governance
Taxonomy Guidelines …1 System with Metadata – Taxonomy Management System - Audience: Know thy user for they are not Thee - Harmony of Purpose - Communication Listening Understanding Consensus vs majority - Metadata for data - Metadata for metadata - Governance Human Element
Taxonomy Guidelines …2 System with Metadata – Taxonomy Management System Jerusalem Artichokes Human Element Courtesy: Wikipedia The OTHER Category
Taxonomy Guidelines …3 System with Metadata – Taxonomy Management System Human Element Defining relationships among metadata and data elements: First step toward semantics Vehicle Applies-To Manufactured-in EMISSION RULES Observed-In CITY
Taxonomy Guidelines …4 System with Metadata – Taxonomy Management System Human Element • Knowledge worker Participation • Buy-in from management • Buy-in from other affected departments
TaxoConsolidator Source 1 Source 2 Master Taxonomy TaxoConsolidator allows user to create a Master taxonomy by combining (adding and merging through dragndrop) individual taxonomies created by knowledge workers Courtesy: RealTechInc
Wordmap – Taxonomy Management System Creating and maintaining taxonomies Using Wordmap Courtesy: Earley & Associates
Moving toward semantics • Understand your audience • Define the domain of problems clearly • Need for robust representation of data, information in that domain • Involve all relevant knowledge workers • Create a taxonomy – with metadata and relationships • Expose and use the taxonomy in systems enterprise wide • Need for a flexible rules and inference engines to interpret data and discover related “knowledge”
Next Steps toward semantics Enterprise Systems (documents, database) Taxonomy Mangement System (Taxonomy) Rules Inference Engines (Semantic Interpreter) Information Access Systems (Search) Human Element
New Tools for Taxonomy New Tools - TaxoBuilder – term extraction tool and individual taxonomy construction tool • TaxoConsolidator – consolidates individual taxonomies • Wordmap from E&A
Summary • Search and understanding user request through query semantics • Represent your information through taxonomies as a fulcrum for all information management in enterprise • Build semantic interpreters of relationships and metadata to complement search