Improving Navigation and Findability Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services

2 Agenda  Introduction  Semantics, Taxonomy, and Faceted Navigation Key Ideas  Review of Media Sites – Key Elements – Common Themes – What Works and What doesn’t  Development Guide – Semantics and Faceted Navigation  Conclusion

3 KAPS Group: General  Knowledge Architecture Professional Services  Virtual Company: Network of consultants –  Partners – Business Objects SA, Endeca, Interwoven, FAST, etc.  Consulting, Strategy, Knowledge architecture audit  Taxonomies: Enterprise, Marketing, Insurance, etc.  Services: – Taxonomy development, consulting, customization – Technology Consulting – Search, CMS, Portals, etc. – Metadata standards and implementation – Knowledge Management: Collaboration, Expertise, e-learning – Applied Theory – Faceted taxonomies, complexity theory, natural categories

4 Semantics and Facets: Key Ideas Real Key – All of the above  Facet – orthogonal dimension of metadata  Taxonomy - Subject matter / aboutness  Ontology – Relationships / Facts – Subject – Verb - Object  Software - Text analytics, auto-categorization  People – tagging, evaluating tags, fine tune rules and taxonomy, social tagging, suggestions  Enterprise Search Summit Sourcebook – A Knowledge Architecture Approach to Search

5 Essentials of Facets  Facets are not categories – Categories are what a document is about – limited number – Facets are types of metadata attributes  Facets are orthogonal – mutually exclusive – dimensions – An event is not a person is not a document is not a place.  Facets – variety – of units, of structure – Numerical range (price), Location – big to small – Alphabetical, Hierarchical – taxonomic  Facets are designed to be used in combination Wine where color = red, price = excessive, location = Calirfornia, And sentiment = snotty

6 Advantages of Faceted Navigation  More intuitive – easy to guess what is behind each door Simplicity of internal organization 20 questions – we know and use  Dynamic selection of categories Allow multiple perspectives  Systematic Advantages – fewer elements – 4 facets of 10 nodes = 10,000 node taxonomy – Ability to Handle Compound Subjects  Flexible – can be combined with other navigation elements

7 Essentials of Taxonomies  Formal Taxonomy – parent – child relationship – Is-A-Kind-Of ---- Animal – Mammal – Zebra – Partonomy – Is-A-Part-Of ---- US-California-Oakland  Browse Classification – cluster of related concepts – Food and Dining – Catering – Restaurants  Taxonomies deal with semantics & documents – Multiple meanings and purposes – Essential attributes of documents are not single value  Taxonomies combined with facets – Supports an essential way of thinking – Can get value with smaller taxonomies – Formal taxonomies tend to work better

8 Essentials of Ontologies  Facts – Subject – Verb – Object – Fred isa Vice-President  Relationships – Vice-Presidents - Have Employees & Bosses  Implications Vice-Presidents - Make more than managers  Knowledge Representation – XML, RDF / OWL / Inference Rules  Knowledge Based Reasoning Applications  Technology in search of a business model – Knowledge is really hard

9 Dynamic Classification / Faceted navigation  Search and browse better than either alone – Categorized search – context – Browse as an advanced search  Dynamic search and browse is best – Can’t predict all the ways people think Panda, Monkey, Banana – Can’t predict all the questions and activities China and Biotech Economics and Regulatory

10 Sample eCommerce Sites  Pure Facets – Product Catalogs – Library Catalogs  Traditional Search  Search and Categories  Facets, Taxonomies, and Semantics,

11 Three Environments: E-Commerce

12 Three Environments: E-Commerce

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23 eCommerce Common Themes  Balance of commerce and information  Source and Type are basics  Standard Facets – People, Companies, Place, Industry  Interactive interface – sliders, date ranges  Taxonomy – just another facet? – Keywords vs. simple taxonomy  Semantics still hardest – summaries, related, rank  Tag Clouds / Clusters – how useful?

24 eCommerce: Issues  Balance of information and ads – Advertiser dominance – No – Auto-ads – Obituary for Obama  1 or 2 filters (source / type) – No – Intersection of facets is source of power  Facets not orthogonal – topics and issues  Good Information Architecture – Space wars – summary or full facet display – Simplicity vs. research power  Integrated design – Complex, not complicated

25 Integrated Design – Facets & Semantics Design Issues - General  What is the right combination of elements? – Faceted navigation, metadata, browse, search, categorized search results, file plan  What is the right balance of elements? – Dominant dimension or equal facets – Browse topics and filter by facet  When to combine search, topics, and facets? – Search first and then filter by topics / facet – Browse/facet front end with a search box

26 Semantics and Facets: Development Elements – More Metadata!  Text Analytics Software – Entity / Noun Phrase – metadata value of a facet feeds facets, signature, ontologies – Taxonomy and categorization rules Auto-categorization – feeds subject facets  Variation of eCommerce and Enterprise – When and how add metadata, additional facets – CM – Hybrid of taggers, software, and policy – Software offers suggested categorization, facet values – Relevance – best bets to ontology based relevance

27 Semantics and Facets: Development Software Tools – Auto-categorization  Auto-categorization – Training sets – Bayesian, Vector Machine – Terms – literal strings, stemming, dictionary of related terms – Rules – simple – position in text (Title, body, url) – Advanced – saved search queries (full search syntax) – NEAR, SENTENCE, PARAGRAPH – Boolean – X NEAR Y and Not-Z  Advanced Features – Facts / ontologies /Semantic Web – RDF + – Sentiment Analysis – positive, negative, neutral

28 Semantics and Facets: Development Software Tools – Entity Extraction  Dictionaries – variety of entities, coverage, specialty – Cost of update – service or in-house – Inxight – 50+ predefined entity types – Nstein – 800,000 people, 700,000 locations, 400,000 organizations  Rules – Capitalization, text – Mr., Inc. – Advanced – proximity and frequency of actions, associations – Need people to continually refine the rules  Entities and Categorization – Total number and pattern of entities = a type of aboutness of the document – Bar Code, Fingerprint

29 Conclusions  Documents – more complicated than products, later start – Need facets plus taxonomies, semantics  Integrated design is essential – not facets as add on  Semantics is still not there – hardest, but some progress  Text Analytics (Entity extraction and auto-categorization) are essential  Future – new kinds of applications: – Text Mining, research tools, sentiment  Future of Search – smart ways to refine results, not better relevance – Real problem with 10 mil hits – no way to get to target – Include facets, taxonomies, semantics, & lots of metadata

Questions? Tom Reamy KAPS Group Knowledge Architecture Professional Services