Webinar: Metadata Enrichment in Publishing

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Metadata Enrichment in Publishing: Boosting Productivity and Increasing User EngagementOntotext webinar series 29th of October 201511am ET | 10am CT |8am PT | 1500 UTC

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AgendaCompany infoMetadata challengesOntotext approach to metadata enrichment Dr. GeorgievLive demosWrap up + QnAOct 2015Metadata Enrichment in Publishing2

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Company essentialsOne-stop shop for semantic technologyText Analytics + Content Enrichment + Search + Graph Database EngineOver 400 person-years in R&D Started in year 2000As R&D lab within Sirma the biggest Bulgarian software companyGot spun-off and took VC investment in 2008 70 staff, growing revenue, profitableHQ in Sofia, Bulgaria, offices in London and NYCOct 2015Metadata Enrichment in Publishing3

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Company essentialsWhy? enable better search, analytics and content deliveryWhat? data and content management technologyHow?semantic analysis of text, NoSQL graph databaseBest for:content publishing and information discoveryOct 2015Metadata Enrichment in Publishing4

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Clients (selection)Oct 2015Metadata Enrichment in Publishing5

Major financial Information agencyMajor business and legalInformation agency

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What others are saying about metadata"Metadata Matters" Bloomberg white paper, 2014Metadata was once purely the domain of the tech team, today it affects everyone in a media and publishing organizationsfrom editorial team members to business leaders." John O'Donovan, Former CTO of Financial Times"Everyone forgets about metadata. All your assets are useless to you unless you have metadata your archive is full of stuff that is of no value because you cant find it and dont know what its about.A manifesto on metadata, Thad McllroyThe only way to make publishing's great content discoverable, is "via rich metadata linked into smart search systems."Oct 2015Metadata Enrichment in Publishing6

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Types of metadataStructural metadata Technical metadataDescriptive metadataAdministrative metadataRights metadataCommercial metadataOct 2015Metadata Enrichment in Publishing7

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Technical metadata

Examples of enrichment of technical metadata

Tagasauris saw the potential for a semantic engine like GraphDB to add value and intelligence to their tagging services.Oct 2015Metadata Enrichment in Publishing8

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Descriptive metadata

Examples of enrichment of descriptive metadata

With semantic metadata you can describe your content in terms of the locations, people, organizations, brands, etc that the content is about.Oct 2015Metadata Enrichment in Publishing9

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The risk of being negligent to your metadataThe failure to adequately account for each type of metadata can affect a publishing companys ability to efficiently create, store, find, access and publish content of all types!"Metadata Matters" Bloomberg white paper, 2014

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Why do we need to care more about metadata?etadata drives content organization, workflow optimization and automation

Its economically smarter to tie assets together throughout the supply chain with metadataOct 2015Metadata Enrichment in Publishing11

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Typical publishing workflow

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Semantic publishing workflow

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Why do we need to care more about metadata?A strong metadata system can power centralized searches, helping find assets across data silos

If an asset can be easily found, it can be reused and repurposed more easilyOct 2015Metadata Enrichment in Publishing14

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Easily discover all your content assets

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Metadata can empower automationMany publishers still rely on big teams of editors to manage their digital offerings while at the same time

A single editor could aggregate all content that relates to particular topic and with appropriate metadata tagging that could happen automaticallyOct 2015Metadata Enrichment in Publishing16

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Use case: BBCGoalsCreate a dynamic semantic publishing platform that assembles web pages on-the-fly using a variety of data sourcesDeliver highly relevant data to web site visitors with sub-second responseChallengesBBC journalists author and publish content which is then statistically rendered. The costs and time to do this were highDiverse content was difficult to navigate, content re-use was not flexible

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"The goal is to be able to more easily and accurately aggregate content, find it and share it across many sources. From these simple relationships and building blocks you can dynamically build up incredibly rich sites and navigation on any platform." John ODonovan, Chief Technical Architect, BBC

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Metadata can greatly enhance discoverabilityUnited metadata across multiple data silos can provide a universal search solution for editors looking for specific content internal usage and search

Publishers need to take full advantage of traffic from search to better expose and potentially monetize their contentOct 2015Metadata Enrichment in Publishing18

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Use case: EuroMoneyOct 2015Metadata Enrichment in Publishing19GoalsCreate a horizontal platform to serve 100 different publications Platform which would include the latest authoring, storing, and delivery technologies including, semantic annotation, search and a triple store repositoryChallengesMultiple domains covered Sophisticated content analytics including relation, template and scenario extraction

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Metadata can drive user engagementRecommendation engines also rely on metadata to suggest content to users

So, ultimately, the better structured and more accurate the metadata, the more likely recommended content to be highly relevant

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Use case: Financial TimesOct 2015Metadata Enrichment in Publishing21GoalsCreate a horizontal platform for both data and content based on semantics and serve all functionality through this platformChallengesCritical part of FT.COMPersonalized recommendation based on user behavior and semantic context (Related Reads)

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Ontotext value propositionMake Text and Data Tango Together!Today there is an artificial divide between text and data Semantic technology removes the divide and brings them together

We interlink text and data to unveil their meaningLarge knowledge graphs help text-mining!Interlinking text and data allows us to add context and meaning to both

We deliver unmatched search and explorationAcross all sorts of data and at a fraction of the cost of alternative approaches

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ONTOTEXT Technology:Analyzing TextOct 2015Metadata Enrichment in Publishing23Full spectrum of NLP capabilitiesSemantic indexingTag references with entity IDsGenerate semantic metadata descriptions of documentsStore metadata in GraphDB

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ONTOTEXT Technology:Interlinking Text and DataOct 2015Metadata Enrichment in Publishing24Use large knowledge graphs for text analysisSemantic annotation and searchCombine structured database queries with full-text search and inference

We make sense of text and data by linking and interpreting them together

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Methodology

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Zoom in 25

Methodology

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Methodology

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Domain model design Information architecture, a combination of the work of an architect and the knowledge of a subject matter expert. 27

Example KB for 50 daily publications

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Example KB Newz 28

Methodology

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Initial Concept Extraction Pipeline29

Design of Machine Learning Pipeline

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Iterative implementation of ML-driven extraction 30

Continuous AdaptationOct 2015Metadata Enrichment in Publishing#31

Continuous adaptation of the text analytics modules / concept extraction services. Initial creation of gold standards and then adapting the ML models according to new examples and editorial feedback. 31

Examples: Semantic Content EnrichmentOct 2015Metadata Enrichment in Publishing32

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Examples: Semantic Content Enrichment (live)Oct 2015Metadata Enrichment in Publishing33

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Examples: Faceted Search-Co-occurrence (live)Oct 2015Metadata Enrichment in Publishing34

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Examples: Key Entities & Trends (live)Oct 2015Metadata Enrichment in Publishing35

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Proven in Publishing and Other SectorsApplication: Content production and deliveryHelping for: authoring, enrichment, presentation, re-purposing, personalized recommendationApplication: Information discovery Powerful semantic enterprise search for applications like regulation compliance and drug safetyValuable collection of use cases: 10+ high-profile projectsBusiness news: FT, Bloomberg, EuromoneyScientific publishing: John Willie & Sons, Oxford University Press, IETMedia & content publishers: BBC, DK, Getty, Disney, ...Oct 2015Metadata Enrichment in Publishing36

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Semantic News Publishing SolutionOct 2015Metadata Enrichment in Publishing37

They have tons of great contentThat is expensive to manage and reuseBut struggle to engage readersHard to compete with social networks and other online and mobile channelsSolved by OntotextDynamic topic aggregation & feed generationPersonalized recommendations

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Scientific Publishing SolutionOct 2015Metadata Enrichment in Publishing38

They have tons of legacy static contentThat is expensive to manage and reuseAnd struggle to monetize their contentHard to compete with platforms providers and open access resourcesSolved by OntotextSmarter search and recommendationsTaxonomy, Thesauri, Vocabulary enrichmentDynamic content aggregation

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Personalized Learning SolutionOct 2015Metadata Enrichment in Publishing39

They have tons of static contentThat is expensive to manage and reuseAnd struggle to engage learners and educatorsHard to compete with the ed-tech companies and free e-learning resourcesSolved by OntotextMapping of learning resources to curriculaDynamic content aggregationPersonalized learning

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Wrap upUnique Technology PortfolioTop notch RDF graph database and text-miningOne-stop shop for content enrichment and metadata managementEnd-to-end solution for Media and PublishingAuthoring, curation and publishing through adaptive text-miningProven to Deliver we run FT.COM and BBC.CO.UK/SPORTStable, Sustainable and Growing CompanyOct 2015Metadata Enrichment in Publishing40

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Thank you!Experience the technology with NOW: Semantic News Portalhttp://now.ontotext.com

Try out our Semantic tagging servicehttp://tag.ontotext.com

Learn more at our website or simply get in touch info@ontotext.com, @ontotextOct 2015Metadata Enrichment in Publishing41

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