Semantic Content Infrastructure for Knowledge Applications Tools of Change 2011 Thane Kerner, CEO

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Semantic Content Infrastructure for Knowledge Applications Tools of Change 2011 Thane Kerner, CEO Silverchair. 1. Basics of Semantic Content 2. Dynamic Concept-Based Relationships 3. Semantically-Driven Behavioral Analysis 4. Application Ecosystem. N-Tier Basics. N-Tier Basics. - PowerPoint PPT Presentation

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Semantic Content Infrastructurefor Knowledge Applications

Tools of Change 2011Thane Kerner, CEOSilverchair

1. Basics of Semantic Content

2. Dynamic Concept-Based Relationships

3. Semantically-Driven Behavioral Analysis

4. Application Ecosystem

N-Tier Basics

N-Tier Basics

N-Tier Basics

N-TierPublishing

N-TierPublishing

N-TierPublishing

Taxonomic Normalization

Chapter 23: Numbness, Tingling, and Sensory LossNormal somatic sensation reflects a continuous monitoring process, little of which reaches consciousness under ordinary conditions. By contrast, disordered sensation, particularly when experienced as painful, is alarming and…

For Humans

<semantics controlvocab=“UMLS”> <tag> <root-term termID="28648">sensation disorders</root-term>…

For Computers

“disordered sensation” = 215 PubMed results“sensation disorders”

= 112,577 PubMed results

<title>

<author>

<abstract>

<reference>

<section>

<topic=panic disorder>

<topic=therapy>

<topic=evidence quality>

GranularSemanticMetadata

DynamicConcept-BasedRelationships

Ontological expression

<drug=rosiglitazone>

<is risk factor for>

<condition=myocardial infarction>

Behavioral Analysis to Improve Relevance

O6AE-9D3-F412

Application Ecosystem

Production approach“Here’s how we do that semantic thing.”

Application approach“Here’s how we create a more useful and compelling service for our customers.”

Information Criticality

Health care

Biz Comm (email, etc.)

Shopping

General News

Professional Info / Research

Medical point of care

CommoditizationMistrustAbandonmentBad outcomesMalpractice

Accuracy Threshold

Relative Accuracy

Req’d Entertainment

Taxonomic Approach to Content Enrichment

• Add a Domain-Aware Dimension to Text Mining Techniques

• Developed Technology Based on Domain… LanguageRelationshipsProcesses and Use Cases

The Domain-Aware Approach

<optimal semantic metadata>

Knowledge Domain Abstraction (Taxonomy and Ontology)

Statistical Text Mining

(NLP)

UserInputs

Taxonomic Content Inputs

Scaled Content Enrichment

Vocabulary control

Real-time query expansion/normalization; navigation; related concepts; etc.Swiss SOAP XML API

Concept Identification

Significance Weighting

Search query logs; user activity logs; content phrase analysis, taxonomy interaction analysis

Content gap analysis

Publisher Web Applications

Publisher Content Repository

Tagmaster Automated Tagging System

Content Import/Export Integration Layer

(Including Editorial Review & Validation)

Cortex TaxonomyHierarchical relationshipsUMLS/standards mapping

Equivalents ServerSynonyms/Alt phrasing Acronyms/Jargon

Totem Taxonomy & Thesaurus Manager

+

Custom TaxonomiesCustom collection mappingLocal/proprietary terms

+

XML Web Services(Swiss Context Server)

Taxonomy/Collections Management Group

Semantic Services Architecture

User Behavior Inputs

thanek@silverchair.com

Tools of Change 2011Thane Kerner, CEOSilverchair

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