SEO and IA: The Beginning of a Beautiful Friendship

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Search technology and IA have developed on parallel tracks over the last many years. I propose that they join forces in creating an enhanced user information finding experience and present specific …

Search technology and IA have developed on parallel tracks over the last many years. I propose that they join forces in creating an enhanced user information finding experience and present specific opportunities for deeper IA engagement.

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  • Suxus Technology | Web Design In Tirunelveli | Tirupur | Trichy | Seo‎
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  • 1. 2007 IA Summit: Las Vegas SEO and IA: The Makings of a Beautiful Friendship
  • 2. Introduction
    • Me: Information architect/Search specialist
      • IA since 1998
      • Search since 2004
    • Topic: Search engine optimization and IA
      • Shift in user locus of attention
        • From navigation to search box
      • Shift in our locus of attention
        • From macro-structure to micro-wayfinding
    • What I want
      • IA to become a partner in developing search technology that works with the user
      • IA community to “think” about how users find their websites when they design them
      • Key takeaways [fingers crossed at my end]
        • Search optimization and IA can and should co-exist
        • One should not exist at the expense of the other
  • 3. Search Usability
    • Web analytics show preference for search box over any site navigation of any kind
      • Search enables users to develop a need-specific/use-specific information path
    • Search engine users visit more pages than those using navigation
      • Pogo effect
      • now offers preview service so user does not have to click through
        • How much of the navigation will they see in a thumbnail?
    • Out of the top 20 results and you are out of sight and out of mind for a majority of users
  • 4. Blame it all on Google
    • PageRank is a pre-query valuation
      • Based on number of links to the page
        • 1 link=1 vote
        • Most votes wins top placement
      • Has no relationship to the subject of the query
    • Googlearchy : dominant Web sites become more firmly entrenched in search results by nature of size
      • Link rich get richer
    • Failings soon uncovered
      • Link farms
      • Googlehacks
  • 5. Search 2.0
    • Web 2.0 give us Search 2.0
      • Harnessing the collective intelligence
        • Online bookmarking
      • Architecture of participation
        • Open source Search
        • Peer-to-peer Search
          • Index of nodes in system
          • Query passed to find appropriate node
      • Remixable data sources and data transformation
        • Local search
        • Any of the “maps” applications
        • and other travel sites
      • Software above the level of a single device
        • Mobile search
    • Compensation for the commercialization of organic search
      • Paid ads do not have to map semantically to the results they accompany
      • Wales and Searchipedia
        • Program not tied to a revenue model
  • 6. Now It is All About Meaning
    • As Moore’s Law brings about cheaper, faster, stronger hardware, the quest changes from indexing everything to the presentation of results
    • Search challenge to determine relevance without understanding meaning
    • Transition from strict computation to computational techniques to determine meaning
      • Hilltop Algorithm
      • Topic-sensitive PageRank
  • 7. Hilltop Algorithm
    • Segmentation of corpus into broad topics
      • Subset that is then extrapolated to Web as a whole
      • Created by Jon Kleinberg at Cornell in late 1990s
        • Consultant to Google
    • Selection of authority sources within these topic areas
      • Authorities have lots of non-related pages on the same subject pointing to them
      • Quality of links more important than quantity of links
    • Determination of HUBS
      • Pages that point to many authority sources
    • Pre query calculations applied at query time
    • Likely part of Google’s Florida update in 2004
  • 8. Topic-Sensitive PageRank
    • Consolidation of Hypertext Induced Topic Selection [HITS] and PageRank
    • Pre-query calculation of factors based on subset of corpus
      • Context of term use in document
      • Context of term use in history of queries
      • Context of term use by user submitting query
    • Creator now a Senior Engineer at Google
  • 9. Search Further Down the Road
    • Semantic search technology patents
      • Search tool with preset categories and keywords
        • 4-part database of information
          • Index, categories, keywords, document-specific data
        • Categories define topics through human-mediation
        • Keywords extracted from document text
        • User can iterate search results through related keywords presented from database
      • Search manager
        • Brokering application that facilitates selection of best search engine for the user’s query
      • Similarity estimation
        • Creates “sketch” or compact representation
        • Compares sketches based on determined similarity threshold
        • Deleted duplicate entries
      • Personalized search
        • Microsoft: Compares snippets of Web search engine results with data collected from user behavior and client
          • Demonstrated in NYT article March 7, 2007
        • Google: user bookmarks [online and client] used to construct “personalized search object” that is used to filter Web search result
    • Predictive search
      • Bayesian model
      • Compares user choices to predict more appropriate result from same vector space
  • 10. SEO and IA: Choices
    • Capitulate
      • No action
      • Search technology continue on parallel path
    • Cooperate
      • Work with current search technology
      • Develop best practices that build on developments in search technology
    • Initiate
      • Influence development of search technology
      • Become a partner in developing user-centric search technology
    • Action Items
      • Influence the technology to work for not against user
        • Site Navigation Strategy
        • Site Organization Strategy
        • Link Strategy
        • Page Code Strategy
        • Content Strategy
        • Metadata Strategy
  • 11. Initiate: Site Navigation Strategy
    • Locus of attention has changed from navigation to search
      • Hard-coded navigation structures are losing ground to pogo strikes
        • Navigation Blindness
        • Navigation Fatigue
        • Page Paradigm
        • Transitional Volatility
    • Users need inducement to move further into the site
    • Search technology rewards relationship navigation
      • Berrypicking Information Model
    • System approach to navigation development
      • Systems have specific behaviors and outcomes
  • 12. Initiate: Site Organization Strategy
    • Distance makes a difference
    • Hierarchy reflects relevance
    • MOSS 2007 and use of structural factors
      • URL depth: the further from the homepage, the less important it must be
      • Click distance: the further from an authority page, the less important it must be
    • Architecture extends from the site to the page
  • 13. Initiate: Linking Strategy
    • Links are human-mediated relationships
      • Blast services are no longer worthwhile
    • Related sites, niche directories, online bookmarking sites, provide starting points
    • Create link-based relationship model of relevance
      • Create or find authority
      • Hook up to HUBs
      • Think beyond the site
  • 14. Cooperate: Page Code Strategy
    • Reveal the site to the search technology
      • Sitemap.xml
    • Provide on the page navigation
      • Don’t rely on dynamic navigation that spider cannot read
    • Craft structures that cue technology on importance
    • Illuminate the non-textual functionality
        • Optimize JScript and Flash
  • 15. Initiate: Content Strategy
    • Dense, subject-specific content is what is indexed
      • People will scroll
      • If they don't scroll, they will print it out
    • Content to code ratio of 25%
    • Promote a keyword-to-content ratio 10–15%
    • Design on-the-page structure to move important information to the top
    • Design relational content models
      • Next steps as well as more information
    • Develop authority sections on site
      • Topic-based, not type-based
  • 16. Cooperate: Metadata Strategy
    • Many forms of description
      • In the code
        • Page title [in the browser window]
        • Description
        • Keywords?
      • In the content
        • Display title
        • Content headings
    • Most effective if unique to the content on the page
      • Say goodbye to cut and paste
    • Description rivals structure for importance for user context
      • thumbnails
    • Humans determine the “meaning” of the document and inform the machine
  • 17. SEO and IA: Threats and Opportunities
    • Threats
    • Search technology advances without user representation
    • Search engines have become dominant navigation tool through information spaces
      • Bountiful
      • Relevant?
    • Traditional IA methodology increasingly less useful
      • Hierarchy: pages further from the home page deemed less important
      • Hard-coded navigation: not visible to search engines
      • Not Authority-based
    • Opportunities
    • Users seeking human-mediated guides to find information
    • Current search rewards a more flexible and intuitive IA
    • Replaced by a new structural paradigm based on relationship and context
      • Hub and authorities
      • Quality over quantity
      • Birds of a feather subject-wise
  • 18. Marianne Sweeny [email_address]