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Improving Search with Taxonomy AIIM Minnesota Chapter  Control:  The Content Management Expo January 26 th , 2009 Seth Earley 781-444-0287 [email_address]
Seth Earley, Founder, Earley & Associates, Inc. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Precise access to information, enabled by consistent organisation
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],What is it? How does taxonomy help? When do I use it? How do I implement it?
Search as Utility ,[object Object],[object Object],These are misleading concepts.  Search is used as a utility, but contexts vary so widely that “plugging search in” does not always produce satisfactory results.
Search and the Hype Cycle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],1 2 3 4 5 Source: http://www.gartner.com
Basic Premises  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Basic Premises  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Basic Premises  ,[object Object],[object Object],[object Object],[object Object]
“… search terms are short, ambiguous and an approximation of the searcher’s real information need…”  ,[object Object],[object Object]
The Challenge of Search ,[object Object],[object Object],[object Object],[object Object]
Search is complex Enterprise search is diverse – need to access multiple applications and contexts – both structured and unstructured Business Intelligence/Analytics Customer Relationship Mgt Document repositories Custom databases and applications Intranets/web pages
Search is Heterogeneous Search/Tagging/Taxonomy Integration Framework Data Sources Search Mechanisms Appliances Federated  Search Auto categorization/ Clustering Entity  Extraction Faceted  Search Semantic  Search Business Intelligence Customer Relationship Mgt Document repositories Custom databases and applications Intranets/web pages
Change is constant ,[object Object],[object Object],[object Object],[object Object],[object Object]
Contributing factors ,[object Object],[object Object],[object Object],[object Object],[object Object]
What is the right balance? ,[object Object],[object Object],[object Object],[object Object]
Different tools create different content structures © 2007 More Structured Email Instant Messages Wikki’s Blogs Discussions Collaborative Workspaces Online Learning Instructor Led Courses Content Mgt Workflow systems Doc Mgt Systems Records Mgt Systems Knowledge Creation Knowledge Access/Reuse Chaotic Processes  Controlled Processes Less Structured
Relative value Lower Cost Higher Cost Message text External News Example deliverables Discussion postings Interim  deliverables Content Repositories Success Stories Benchmarks Approved Methods Best Practices Unfiltered Reviewed/Vetted/Approved Lower Value Higher Value Formal Tagging/Organizing Processes (More difficult to access) (Easier to access) Social tagging (“folksonomy”) Structured tagging (taxonomy)
Taxonomy, Metadata and Content Foundational concepts for effective search
Taxonomy is a foundation… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Goals of a taxonomy ,[object Object],[object Object],[object Object],[object Object],[object Object]
What is metadata? ,[object Object],[object Object],[object Object],[object Object],Taxonomies are the organizing principle behind metadata and the values that populate metadata fields
What is a content model? ,[object Object],[object Object],Title Description Simple content object model *Content model refers to overall framework Content object model refers to a specific model for a set of document types I.e., an overall “Content Model” includes multiple Content Object Models”
Metadata for a product page in a content management system   Title Date Author Features Product_Name Category Doc_ID Doc_Type “ is – ness” “ about – ness” FAQ Product  Press release Specification Promotion
Content modeling – Policy example Title Date Author Subject Doc_ID Content_ID Date Content_ID Date Content_ID Date Standard Header Policy content type Customer Service content type Claims processing content type
Deriving a content model ,[object Object],[object Object],[object Object],[object Object]
© 2007
© 2007
Why the metadata tutorial? One word:  faceted search
Faceted Search/Guided Navigation Or – It’s a dessert, it’s a floor wax, it’s both!
Navigational taxonomy Taxonomy can be a hierarchical grouping of navigational nodes on a web site Challenge is there is no “one way” to navigate that is correct.  Is this the “correct” way?
Navigational taxonomy Or is this one “correct”?  Or is this one?
Motorola.com => United States => Government => Portable Radios Motorola.com => Portable Radios => United States => Government Motorola.com => Government => Portable Radios => United States
Navigating with “facets” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Product type Geographic  region “ Facet” is a top level category in the taxonomy Just three nodes with 5 terms each could have 3 to the 5 th  power (243) possible combinations Vertical market Target document:  P = Portable radio G = United States V = Government
Faceted search implies tagged content with nice structured metadata… What if we don’t have a lot of existing metadata?  Does that mean hire bunch of people to enter it in?  Manual tagging is rarely practical with large amounts of lower value content.  Instead, we need to derive implicit metadata from content
All search leverages metadata… ,[object Object],[object Object],[object Object],[object Object]
All search leverages metadata… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Relevance ranking , for example, is additional metadata for a result that is ‘implied’ or derived based on incoming connections to a piece of content.
Context as metadata ,[object Object],[object Object],[object Object]
Examples of implicit metadata: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context as metadata ,[object Object],Search results organized by repository This is a form of “federated” search – a single search term fed to multiple repositories Example courtesy of Morrison and Foerster
Structure as metadata ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object]
Why you will not “just get Google”  ,[object Object],[object Object],[object Object],[object Object]
Google’s search appliance is leveraging taxonomy values ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Configuration process ,[object Object],[object Object],[object Object],[object Object],Need to consider taxonomy, metadata and thesaurus entries, for example a trigger may include equivalent terms:  lax airport  conditions  SFO airport  delays  newark airport  status  See: http://code.google.com/enterprise/documentation/oneboxguide.html
We still have a context problem “ Revenue” is an ambiguous term
Why doesn’t Google, just use Google?
Why you will not “just get Google”
Applying a taxonomy to search ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Taxonomy & search strategies  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Taxonomy and Search Strategies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object]
Tuned Search ,[object Object],[object Object],[object Object]
Best Bets Example – Best Buy
Tuned Search “Best Bets” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Best Bets Example – SAP.com ,[object Object]
Tuned Search “Best Bets” ,[object Object],[object Object],[object Object],[object Object]
Circuit City Example ,[object Object]
Circuit City Example ,[object Object]
Circuit City Example ,[object Object]
Tuned search – “Best Bets” ,[object Object],[object Object],[object Object],[object Object]
Tuned Search – “Best Bets” ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object]
Leverage the taxonomy terms as metadata – standard search ,[object Object],[object Object],[object Object],[object Object]
Not all content is created equal (ly?) ,[object Object],[object Object],[object Object],[object Object]
Ranking and Relevance ,[object Object],[object Object],[object Object],[object Object]
Standard search
[object Object]
Leverage the taxonomy terms as metadata - faceted search ,[object Object],[object Object],[object Object],[object Object],[object Object]
Faceted Search Example - Epicurious  © 2007 Facets: Course Cuisine Season Type of dish Prep method Source
Faceted search – PC Connection Each parameter narrows the search result to the most appropriate content.
© 2007 Facets Taxo term values
Faceted search ,[object Object],[object Object],Course Cuisine ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Prep method Target document:  Course = Main course Cuisine = Japanese Prep = Steam
Faceted search ,[object Object],[object Object],[object Object]
[object Object],Washington? People, businesses, locations, dates, etc or may be specific to a particular knowledge domain (chemical entities for example)   Entities:
Taxonomy and Search  ,[object Object],[object Object],[object Object]
[object Object]
Categorize search results using the taxonomy ,[object Object],[object Object],[object Object],[object Object]
Categorize search results using taxonomy “clustering” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clustering Example – Circuit City
Clustering ,[object Object],[object Object]
Why you will not “just get Google”
Clustering ,[object Object],[object Object],[object Object],[object Object],[object Object]
Clustering ,[object Object],[object Object]
Categorizing content Statistical/linguistic Rules-based These documents look similar due to an analysis of word patterns – lets put them into the same group These documents look similar based on some rule that have created (they contain marketing plans and are about the newest widget) lets put them into the same group
Building a Taxonomy Slice from a set of Search Results:  Courtesy of Raritan Technologies www.raritantechnologies.com
[object Object]
Disambiguation of search results ,[object Object],[object Object],[object Object],[object Object],[object Object]
Disambiguation methods ,[object Object],[object Object],[object Object],[object Object]
Disambiguation of search results  Mobile data terminals Handheld computers Network Infrastructure Mobile switches Phones Fixed mobile car phones Mobile phones Software applications Mobile applications Two way radios Mobile radios Intelligent video solutions Mobile video enforcer Mobile video sharing MESH Solutions Multi-radio mobile broadband Mobile Computing Mobile application  Presenting term in multiple contexts mobile
From Associative Relationships
Disambiguation of search results ,[object Object],[object Object],[object Object]
Disambiguation of search results ,[object Object],[object Object]
Disambiguation of search results ,[object Object],[object Object],[object Object],[object Object]
[object Object]
Federated Search ,[object Object],[object Object],[object Object],[object Object]
Term Expansion and Federation  Search Clinical trial leader searches compound data. Enters US Trade  Name of compound. 1 Results All results are presented. 5 Allows Federated Search engine to search associated data sources. 4 Returns names of Clinical Trials associated with compounds. 3 Registry Clinical Trials Registry Generic Chemical Registry returns generic and chemical names. 2
Federated search ,[object Object],Search results organized by repository This is a form of “federated” search – a single search term fed to multiple repositories Example courtesy of Morrison and Foerster
Example Solution: Term expansion Term expansion using public source of terms  (CRISP – “Computer Retrieval of Information on Scientific Projects”)  Courtesy of Raritan Technologies www.raritantechnologies.com Search on – “Hypertension”
Example Solution: Term expansion Term expansion using public source of terms  (CRISP – “Computer Retrieval of Information on Scientific Projects”)   Courtesy of Raritan Technologies www.raritantechnologies.com Search on – “Hypertension” Returns back  – “ High blood pressure”  – “ Congenital High Blood pressure”  – “ Systolic hypertension”  –  etc…
Example Solution: Term expansion ,[object Object],[object Object],Courtesy of Raritan Technologies www.raritantechnologies.com Can be implemented with any search engine and any thesaurus source (spreadsheet, relational database, public source) Search on – “Hypertension” Returns back  – “ High blood pressure”  – “ Congenital High Blood pressure”  – “ Systolic hypertension”  –  etc…  Then executes search to return broader result set
Why you will not just “use a folksonomy” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
earley earley & associates earley & associates inc earley & associates needham, massachusets earley & associates taxonomy earley & associates, inc earley & associates, inc. earley & earley associates earley and associates earley and associates inc earley and associates seth earley and associates taxonomy earley assoc earley associates earley associates address earley associates boston earley associates wordmap earley financial earley jumpstart earley taxonomy earley taxonomy & metadata jumpstart call: managing structured metadata and taxonomies earley.com early & associates early and associates taxanomic classification of the freycinetia taxonimic classification of humans taxonomic and dichotomus taxonomic classification taxonomic classification human taxonomic genus of king cobra taxonomic implementation taxonomies of knowledge taxonomies project roadmap taxonomist job description taxonomy  metadata taxonomy & metadata jumpstart - 2007 taxonomy and  false drops taxonomy and classifiation examples of animals taxonomy and metadata taxonomy and metadata jumpstart taxonomy c taxonomy classification taxonomy classification charts taxonomy community of practice taxonomy consulting taxonomy creation taxonomy creation management taxonomy defined taxonomy deployment taxonomy development process taxonomy implementation taxonomy iqpc taxonomy job description taxonomy maintenance taxonomy management taxonomy management job title taxonomy management tools taxonomy metadata taxonomy models for project management taxonomy of global executives taxonomy of man taxonomy search taxonomy seth early taxonomy structure business organisation taxonomy training taxonomy validation taxonomy(2007) taxonomy, mlis taxonomy/classification.online
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object]
Earley & Associates:  #1 on Google for Silver Mining Tools
Taxonomy Community of Practice Calls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Research Reports and White Papers ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions? Seth Earley [email_address] www.earley.com 781-444-0287
Community of Practice Calls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Research Reports and White Papers ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions? Seth Earley [email_address] www.earley.com 781-820-8080

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Taxonomies And Search Aiim Mn

  • 1. Improving Search with Taxonomy AIIM Minnesota Chapter Control: The Content Management Expo January 26 th , 2009 Seth Earley 781-444-0287 [email_address]
  • 2.
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  • 10.
  • 11. Search is complex Enterprise search is diverse – need to access multiple applications and contexts – both structured and unstructured Business Intelligence/Analytics Customer Relationship Mgt Document repositories Custom databases and applications Intranets/web pages
  • 12. Search is Heterogeneous Search/Tagging/Taxonomy Integration Framework Data Sources Search Mechanisms Appliances Federated Search Auto categorization/ Clustering Entity Extraction Faceted Search Semantic Search Business Intelligence Customer Relationship Mgt Document repositories Custom databases and applications Intranets/web pages
  • 13.
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  • 16. Different tools create different content structures © 2007 More Structured Email Instant Messages Wikki’s Blogs Discussions Collaborative Workspaces Online Learning Instructor Led Courses Content Mgt Workflow systems Doc Mgt Systems Records Mgt Systems Knowledge Creation Knowledge Access/Reuse Chaotic Processes Controlled Processes Less Structured
  • 17. Relative value Lower Cost Higher Cost Message text External News Example deliverables Discussion postings Interim deliverables Content Repositories Success Stories Benchmarks Approved Methods Best Practices Unfiltered Reviewed/Vetted/Approved Lower Value Higher Value Formal Tagging/Organizing Processes (More difficult to access) (Easier to access) Social tagging (“folksonomy”) Structured tagging (taxonomy)
  • 18. Taxonomy, Metadata and Content Foundational concepts for effective search
  • 19.
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  • 23. Metadata for a product page in a content management system Title Date Author Features Product_Name Category Doc_ID Doc_Type “ is – ness” “ about – ness” FAQ Product Press release Specification Promotion
  • 24. Content modeling – Policy example Title Date Author Subject Doc_ID Content_ID Date Content_ID Date Content_ID Date Standard Header Policy content type Customer Service content type Claims processing content type
  • 25.
  • 28. Why the metadata tutorial? One word: faceted search
  • 29. Faceted Search/Guided Navigation Or – It’s a dessert, it’s a floor wax, it’s both!
  • 30. Navigational taxonomy Taxonomy can be a hierarchical grouping of navigational nodes on a web site Challenge is there is no “one way” to navigate that is correct. Is this the “correct” way?
  • 31. Navigational taxonomy Or is this one “correct”? Or is this one?
  • 32. Motorola.com => United States => Government => Portable Radios Motorola.com => Portable Radios => United States => Government Motorola.com => Government => Portable Radios => United States
  • 33.
  • 34. Faceted search implies tagged content with nice structured metadata… What if we don’t have a lot of existing metadata? Does that mean hire bunch of people to enter it in? Manual tagging is rarely practical with large amounts of lower value content. Instead, we need to derive implicit metadata from content
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  • 47. We still have a context problem “ Revenue” is an ambiguous term
  • 48. Why doesn’t Google, just use Google?
  • 49. Why you will not “just get Google”
  • 50.
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  • 55. Best Bets Example – Best Buy
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  • 71. Faceted Search Example - Epicurious © 2007 Facets: Course Cuisine Season Type of dish Prep method Source
  • 72. Faceted search – PC Connection Each parameter narrows the search result to the most appropriate content.
  • 73. © 2007 Facets Taxo term values
  • 74.
  • 75.
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  • 79.
  • 80.
  • 81. Clustering Example – Circuit City
  • 82.
  • 83. Why you will not “just get Google”
  • 84.
  • 85.
  • 86. Categorizing content Statistical/linguistic Rules-based These documents look similar due to an analysis of word patterns – lets put them into the same group These documents look similar based on some rule that have created (they contain marketing plans and are about the newest widget) lets put them into the same group
  • 87. Building a Taxonomy Slice from a set of Search Results: Courtesy of Raritan Technologies www.raritantechnologies.com
  • 88.
  • 89.
  • 90.
  • 91. Disambiguation of search results Mobile data terminals Handheld computers Network Infrastructure Mobile switches Phones Fixed mobile car phones Mobile phones Software applications Mobile applications Two way radios Mobile radios Intelligent video solutions Mobile video enforcer Mobile video sharing MESH Solutions Multi-radio mobile broadband Mobile Computing Mobile application Presenting term in multiple contexts mobile
  • 93.
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  • 98. Term Expansion and Federation Search Clinical trial leader searches compound data. Enters US Trade Name of compound. 1 Results All results are presented. 5 Allows Federated Search engine to search associated data sources. 4 Returns names of Clinical Trials associated with compounds. 3 Registry Clinical Trials Registry Generic Chemical Registry returns generic and chemical names. 2
  • 99.
  • 100. Example Solution: Term expansion Term expansion using public source of terms (CRISP – “Computer Retrieval of Information on Scientific Projects”) Courtesy of Raritan Technologies www.raritantechnologies.com Search on – “Hypertension”
  • 101. Example Solution: Term expansion Term expansion using public source of terms (CRISP – “Computer Retrieval of Information on Scientific Projects”) Courtesy of Raritan Technologies www.raritantechnologies.com Search on – “Hypertension” Returns back – “ High blood pressure” – “ Congenital High Blood pressure” – “ Systolic hypertension” – etc…
  • 102.
  • 103.
  • 104. earley earley & associates earley & associates inc earley & associates needham, massachusets earley & associates taxonomy earley & associates, inc earley & associates, inc. earley & earley associates earley and associates earley and associates inc earley and associates seth earley and associates taxonomy earley assoc earley associates earley associates address earley associates boston earley associates wordmap earley financial earley jumpstart earley taxonomy earley taxonomy & metadata jumpstart call: managing structured metadata and taxonomies earley.com early & associates early and associates taxanomic classification of the freycinetia taxonimic classification of humans taxonomic and dichotomus taxonomic classification taxonomic classification human taxonomic genus of king cobra taxonomic implementation taxonomies of knowledge taxonomies project roadmap taxonomist job description taxonomy metadata taxonomy & metadata jumpstart - 2007 taxonomy and false drops taxonomy and classifiation examples of animals taxonomy and metadata taxonomy and metadata jumpstart taxonomy c taxonomy classification taxonomy classification charts taxonomy community of practice taxonomy consulting taxonomy creation taxonomy creation management taxonomy defined taxonomy deployment taxonomy development process taxonomy implementation taxonomy iqpc taxonomy job description taxonomy maintenance taxonomy management taxonomy management job title taxonomy management tools taxonomy metadata taxonomy models for project management taxonomy of global executives taxonomy of man taxonomy search taxonomy seth early taxonomy structure business organisation taxonomy training taxonomy validation taxonomy(2007) taxonomy, mlis taxonomy/classification.online
  • 105.
  • 106. Earley & Associates: #1 on Google for Silver Mining Tools
  • 107.
  • 108.
  • 109. Questions? Seth Earley [email_address] www.earley.com 781-444-0287
  • 110.
  • 111.
  • 112. Questions? Seth Earley [email_address] www.earley.com 781-820-8080