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Rank | Analyse | Lead | Search

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AN INCREDIBLE POWER OF DATA DESCRIBED BY SCHEMA.ORG

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Rank | Analyse | Lead | Search

  1. 1. Rank|Analyse|Lead|Search AN INCREDIBLE POWER OF DATA DESCRIBED BY SCHEMA.ORG Data Science Skills Development Symposium, Edinburgh, June 9th, 2017 Dr. Mirek Sopek
  2. 2. 2FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries INTRO A QUEST FOR MEANING ON THE WEB • The Web is (mostly) a Mess • Metadata becomes (very often) Meta-Crap (after: Cory Doctorow*) • There is no such thing as Esperanto of the Web (despite its importance, English is not a lingua franca) • The trust is lost – people of the Web (often) live in echo- chambers THE WEB WAS IN THE DEEP NEED OF A PRAGMATIC APPROACH SHORTLY AFTER THE WEB WAS INVENTED WE NOTICED THAT: * https://www.well.com/~doctorow/metacrap.htm
  3. 3. 3FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries INTRO WEB FULL OF MEANING INVENTION • The “Web Full of Meaning” was invented (a.k.a. the “Semantic Web” or Web 3.0) • Web gurus borrowed a fundamental term from philosophy – ONTOLOGY - to name their Vocabularies. • Using Ontologies (aka Vocabularies) they started to create and promote new models for Data (Linked Data, Graph Data, Smart Data) TO COUNTERBALANCE THE MESS …
  4. 4. 4FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries INTRO DISSATISFACTION • Most of the results were (so far) only good for academic research • Almost none of our ontologies enjoyed wide adoption • Promises to build Web 3.0 quickly turned out to be failed THE WEB WAS IN THE DEEP NEED OF A PRAGMATIC APPROACH HOWEVER…
  5. 5. 5FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries …SO THE SCHEMA.ORG WAS INVENTED ! • Schema.org (2011), sponsored by the most important search engines: Google, Microsoft, Yahoo and Yandex, is a large scale collaborative activity with a mission to create, maintain, and promote schemas for structured data on the WEB pages and beyond. • It contains more than 2000 terms: 753 types, 1207 properties and 220 enumerations. • Schema.org covers entities, relationships between entities and actions. • Today, about 15 million sites use Schema.org. Random yet representative crawls (Web Data Commons) show that about 30% of URLs on the web return some form of triples from schema.org. • Many applications from Google (Knowledge Graph), Microsoft (like Cortana), Pinterest, Yandex and others already use schema.org to power rich experiences. • Think of schema.org as a global Vocabulary for the web transcending domain and language barriers.
  6. 6. 6FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries http://bl.ocks.org/danbri/raw/1c121ea8bd2189cf411c/ WHAT IS SCHEMA.ORG? http://schema.org
  7. 7. 7FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG USE SIMPLICITY – AN ILLUSTRATION http://finances.makolab.com/HTML/LoanStudents/LoanStudents.html
  8. 8. Under the hoodOF SCHEMA.ORG AND ITS EXTENSIONS
  9. 9. 9FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG • „The driving factor in the design of Schema.org was to make it easy for webmasters to publish their data. In general, the design decisions place more of the burden on consumers of the markup.” R.V. GUHA, D. DAN BRICKLEY, S. MACBETH – „Schema.org - Evolution of Structured Data on the Web” DESIGN DECISIONS • Derived from RDFS (RDF Schema) • Multiple inheritance hierarchy • POLYMORPHIC PROPERTIES - Each property may have one or more types as its domain and its range („domainincludes” and „rangeincludes”) DATA MODEL
  10. 10. 10FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG USAGE MODELS • Under full control of site/messages/data publishers • Data EMBEDDED into page, data representation or into message markup (HTML, XML) • Harvested during standard crawling, message or data processing SERIALIZATIONS • RDFa - CANONICAL • Microdata (native to HTML5) • JSON-LD
  11. 11. 11FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG CORE  HOSTED EXTENSIONS  EXTERNAL EXTENSIONS • CORE – „Core, basic vocabulary for describing the kind of entities the most common web applications need”* • HOSTED/REVIEWED EXTENSIONS – Domain specific basic vocabularies. • EXTERNAL EXTENSIONS – More specialized, fully independent domain specific vocabularies. Built by a third party. • Today: autos, finance, bibliography, health & life-sciences, iot EXTENSION MECHANISM: SEQUENCE OF SPECIFICITY * http://schema.org/docs/extension.html
  12. 12. 12FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG CORE http://schema.org/<term> http://schema.org/<term> HOSTED EXT. http://<ext>.schema.org/<term> http://schema.org/<term> External EXT. http://<ext.domain>/<term> http://<ext.domain>/<term> CORE http://schema.org/Car http://schema.org/Car HOSTED EXT. http://auto.schema.org/Motorcycle http://schema.org/Motorcycle External EXT. http://fibo.org/voc/BusinessEntity http://fibo.org/voc/BusinessEntity EXTENSION MECHANISM: RULES FOR URIs Documentation URI: Canonical URI: Examples: Rules:
  13. 13. 13FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG <div itemscope itemtype="http://schema.org/BankTransfer"> <h1>If you want to donate</h1> Send <span itemprop="amount" itemscope itemtype="http://schema.org/MonetaryAmount"> <span itemprop="amount">30</span> <span itemprop="currency" content="USD">$</span> </span> via bank transfer to the <span itemprop="beneficiaryBank">European ExampleBank, London</span> Put "<i itemprop="name">Donate wikimedia.org</i>" in the transfer title. </div> EXAMPLES - MICRODATA
  14. 14. 14FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG <div vocab="http://schema.org" typeof="BankTransfer"> <h1>If you want to donate</h1> Send <span property="amount" typeof="MonetaryAmount"> <span property="amount">30</span> <span property="currency" content="USD">$</span> </span> via bank transfer to the <span property="beneficiaryBank"> European ExampleBank,London</span> Put "<i property=’name’>Donate wikimedia.org</i>" in the transfer title. </div> EXAMPLES - RDFa
  15. 15. 15FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD OF SCHEMA.ORG <script type="application/ld+json"> {"@context": "http://schema.org/", "@type": "BankTransfer", "name": "Donate wikimedia.org", "amount": { "@type": "MonetaryAmount", "amount": "30", "currency": "USD" }, "beneficiaryBank": "European ExampleBank, London"} </script> EXAMPLES – JSON-LD
  16. 16. 16FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries CREATING EXTENSIONS TO SCHEMA.ORG • Extension URI: auto.schema.org • Designed as the first phase of the GAO project (Generic Automotive Ontology - http://automotive-ontology.org) • First step: extending core vocabulary by a minimal set of new terms (May 2015) • Second step: creating auto.schema.org hosted extension (May 2016) • Third step: creating POC of the external extension (March 2017) • Extension URI: fibo.schema.org • Inspiration from FIBO project (Financial Industry Business Ontology – http://fibo.org ) • Going through BOC (Bag-Of-Concept) phase and using an „Occam Razor” approach. • First step: extending core vocabulary by a minimal set of new terms (May 2016) • Second step: creating fibo.schema.org hosted extension (published in pending.schema.org (March 2017)) • Third step: creating POC of the external extension (March 2017) AUTOMOTIVE EXTENSION FINANCIAL EXTENSION
  17. 17. 17FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries AUTO.SCHEMA.ORG May 13, 2015 – official introduction of the Automotive extension to schema.org Collaborative project of Hepp Research GmbH, MakoLab SA and many other individuals.
  18. 18. 18FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries FIBO.SCHEMA.ORG Extension of the core vocabulary by a minimal set of new terms (May 2016) The hosted extension (published March 2017) as pending.schema.org Collaborative project of an international group of individuals lead by MakoLab SA. Described in: http://schema.org/docs/financial.html
  19. 19. 19FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries The financial extension of schema.org refers to the most important real world objects related to banks and financial institutions: • A bank and its identification mechanism • A financial product • An offer to the client • Described in: http://schema.org/docs/financial.html Thing CLASSES Action TransferAction MoneyTransfer Intangible Service FinancialProduct BankAccount DepositAccount CurrencyConversionService InvestmentOrDeposit BrokerageAccount DepositAccount InvestmentFund LoanOrCredit CreditCard MortgageLoan PaymentCard + PaymentService StructuredValue ExchangeRateSpecification MonetaryAmount RepaymentSpecification FIBO.SCHEMA.ORG
  20. 20. 20FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries FIBO.SCHEMA.ORG The financial extension of schema.org refers to the most important real world objects related to banks and financial institutions: • A bank and its identification mechanism • A financial product • An offer to the client • Described in: http://schema.org/docs/financial.html
  21. 21. 21FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries A BANK A DEPOSIT ACCOUNT A PAYMENT CARD THE BASIC MODELS OF THE FINANCIAL OBJECTS FIBO.SCHEMA.ORG
  22. 22. RankWEB SEARCH REDEFINED
  23. 23. 23FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries FUNDAMENTAL TRENDS IN WEB SEARCH 1. BIGGER SHARE ON THE TRANSACTION 2. RICHER INTERACTION This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  24. 24. 24FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries 4. DYNAMICS AND VOLATILITY 3. STRONGER INDIVIDUALIZATION FUNDAMENTAL TRENDS IN WEB SEARCH This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  25. 25. 25FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries RICH SNIPPETS KNOWLEDGE PANEL VISUAL FEATURES IN SEARCH ENGINES This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  26. 26. 26FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries FACTUAL ANSWERS And more … TABULAR RESULTS VISUAL FEATURES IN SEARCH ENGINES This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  27. 27. 27FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries CONCRETE BENEFITS Rich snippet results on 2nd position received higher CTR than standard snippet on 1st position CTR INCREASE EXAMPLE
  28. 28. 28FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries What you measure in a traditional way may not reflect your actual performance Solutions: • Use KPIs with care • New metrics based on external resources • Add granular event handlers MEASURE WITH CARE NEW METRICS NEEDED
  29. 29. 29FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SUMMARY OF “RANK” BENEFITS OF SCHEMA.ORG • CTR increase (Rich Snippets effect) • Better Brand visibility (Knowledge Panels and Factual Answers) • Better Product positioning (Rich snippets & Tabular results) • Faster way to reach searched content (more sitelinks) • Better mobile device experience of search 11.09.2015 – Google: „Over time, I think it [structured markup] is something that might go into the rankings as well. If we can recognize someone is looking for a car, we can say oh well, we have these pages that are marked up with structured data for a car, so probably they are pretty useful in that regard. We don’t have to guess if this page is about a car.” John Mueller / Webmaster Trends Analyst @Google
  30. 30. 30FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries WHAT ELSE CAN WE DO WITH SCHEMA? • While schema.org was invented to help search engines in their job and to help site owners to be more reliably discovered and ranked on the Search Engine Results Pages – its benefits are much more profound. • This why we say that schema.org power goes beyond RANK, and allows you to ANALYZE your site market environment better, improve site convergence and LEADS generation and helps to deliver a new kind of SEARCH capacity for your site! • What is more, to SEARCH and to ANALYZE you don’t need Google to cooperate 
  31. 31. AnalyseNEW KIND OF DATA ANALYTICS
  32. 32. 32FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS The markup in the website’s code • Schema.org Google Tag Manager • Additional setup Google Analytics • Additional Dimensions and Metrics
  33. 33. 33FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries Auto Model 1 - Name - Brand Version1 Model, fuelConsumption, fuelType, numberOfDoors, Color Version 2 Version 3 Model 2 - Name - Brand Version 1 Version 2 Version 3 Model 3 - Name - brand Version 1 Version 2 Version 3 SCHEMA.ORG DATA IN GOOGLE ANALYTICS POC 1
  34. 34. 34FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS http://wisem.makolab.pl/ga/model1.html
  35. 35. 35FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS http://wisem.makolab.pl/ga/car1a.html
  36. 36. 36FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Google Tag Manager – parsing of the JSON/LD script tag
  37. 37. 37FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Google Tag Manager – sending custom data to GA
  38. 38. 38FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA
  39. 39. 39FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA
  40. 40. 40FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA Which colour of a car should be used in Display Campaigns or in TV ads for Car1?
  41. 41. 41FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS Which engine model of Car1 is most popular online? Should we spend campaign money on Sport version or on Eco version? Usage within GA
  42. 42. 42FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries FINANCIAL EXTENSION SCHEMA.ORG POC • http://finances.makolab.com • Full use of fibo.schema.org • Definitions of financial dimensions • Analytics with Google “GA” POC 2
  43. 43. 43FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries POC’s page Json property Dimension Dimension name BankAccount.html price Bank Account Fee Price name Financial Product Name Financial Product Name BrokerageAccount.ht ml minValue Brokerage Account Minimum Investment Minimum name Financial Product Name Financial Product Name CreditCard.html annualPercentageRate Credit Card APR Percentage Rate minValue Credit Card Required Collateral Minimum price Credit Card Annual Fee Price name Financial Product Name Financial Product Name CreditCard8.html name Financial Product Name Financial Product Name minValue Credit Card Limit Minimum PaymentService.html name Financial Product Name Financial Product Name FinancialProducts.html name Financial Product Name Financial Product Name minValue Minimum Insurence Coverage Minimum maxValue Maximum Insurence Coverage Maximum FINANCIAL EXTENSION SCHEMA.ORG POC
  44. 44. 44FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries TRUE DATA ANALYTICS
  45. 45. 45FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA IN GOOGLE ANALYTICS PROS: CONS: • None.• Analyse additional information available in Schema markup right in Web Analytics. • Better insights into what people look at on the website. Deeper understanding of users’ needs. • Better conclusions for website’s UX optimization. • Better conclusions for campaigns optimization.
  46. 46. LeadNEW KIND OF CONVERGENCE
  47. 47. 47FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries THE PROBLEM OF CONVERGENCE THE PROBLEM • The key benefits of any given website are in the possible ACTIONS clients can make on it to the advantage of the site owner. The most important are the LEAD GENERATION actions. • The clients’ actions depend on many factors and one of the most important is the current customer- journey across the site – because it reflects her/his interests. • However, traditionally, marketers used a flow-chart based approach to define customer journeys • In this approach, the modelling of the customer journey is based on a static map of possible paths a customer may follow • The convergence based on such static approach is insufficient because of unpredictability of customer navigation across the site and lack of knowledge about the customer interests. • In addition to that, flow-chart approach is hard to maintain and modify, because marketers must keep the list of pages that define the journey. This becomes very hard in dynamically changing sites.
  48. 48. 48FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SCHEMA.ORG DATA FOR CONVERGENCE THE SOLUTION and ITS MAIN IDEA GLOSSARY • CTA – Call-To-Action – a specific dynamical element of the page that LEADs the client to specific action, for example to send his contact information, subscribe to a list, chat or decide to buy a product. • Convergence – a certain set of goals the site owner wants to achieve on the site. In most popular case the action that intentionally ends in the customer leaving his contact information. • Intervention point – a page or part of the page where the CTA is invoked • The “LEAD” application uses the format of schema.org (but not necessarily its vocabulary) to enhance site convergence and lead generation. • The markup exposes specific data-points along the customer journey. Many pages may have the same or similar markup. Many different websites can contribute. • The journeys are no longer static or pre-mapped – instead, they are dynamically discovered by the real-time analysis of the path marked by the data-points. • The data collected along the path is used to invoke customer TAILORED CTAs dynamically at the intervention points.
  49. 49. 49FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries MKP 1 MKP 2 MKP 4 MKP 4 MKP 5 MKP 3 MARKING UP CUSTOMER JOURNEY The signals are collected in real-time by the software. The markup (MKP) signals a specific Stage Point on the customer journey
  50. 50. 50FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries MARKING UP CUSTOMER JOURNEY <script type="application/ld+json"> {"@context": "http://schema.org/", "@type": „http://ml.ms/StagePoint", " http://ml.ms/cars": [{ "@type": "PropertyValue", "name": "Professional Cars", "value": „1.0" }, { "@type": "PropertyValue", "name": „Car Audio", "value": „0.5" }] } </script> JSON-LD PROTOTYPE <script type="application/ld+json"> {"@context": "http://schema.org/", "@type": „Person", „http://ml.ms/interest”: [{ "@type": "PropertyValue", "name": „Sport Cars", "value": „1.0" }, { "@type": "PropertyValue", "name": „Car Audio", "value": „1.0" }] } </script>
  51. 51. 51FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries CTAs CALLS AT THE INTERVENTION POINTS INVOKE CTAs based on the client journey across the site CTA 1 CTA 2 CTA4CTA4CTA5CTA3 The CTAs are TAILORED and depend on the signals from the journey.
  52. 52. 52FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries HOW DOES IT WORK? THE ALGORITHM REMARKS • The definition of customer experience along the journey is done on a much higher, abstract level. • This allows for qualitative assignment of CTAs to the different paths. • Multiple pages can signal the same abstract “type of experience” • The parts of the customer journey on separate sites can be taken into account (multi-site experience) • Mark your pages with additional markup that characterizes your customers’ journey across your site (or many sites) • Use special kinds of schema.org property- value pairs to describe a given StagePoint of the journey • Use custom built Tag Manager to invoke tailored CTAs at well defined intervention points. • The underlying backoffice system decides whether and what type of CTAs are called.
  53. 53. SearchADD SMART SEARCH TO YOUR SITE
  54. 54. 54FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP Mark your product data with schema.org markup Run the smart Search Crawler for an Enterprise Website Check for schema.org markup (Microdata or JSON-LD) When markup is found, create property map and assign values Display enhanced search results
  55. 55. 55FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries Corporate product page + microdata http://nusil.com/product/r-2370_rtv-silicone-rubber-foam INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  56. 56. 56FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries UNDER THE HOOD… Crawler Indexer (Lucene) Microdata found Semantic Data WebSite INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  57. 57. 57FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SEARCH AGAINST BOTH CONCEPTS AND THEIR PROPERTIES’ VALUES The real values taken from existing data found by crawler within the marked website pages INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  58. 58. 58FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries SEARCH AGAINST MULTIPLE CRITERIA INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  59. 59. THANK YOU Full slide deck at: http://ml.ms/ds_edi
  60. 60. 60FOR Data Science Skills Development Symposium, Edinburgh, FROM The Leaders in Smart Data for Automotive & Financial Industries PLEASE CONTACT US! MakoLab SA DR. MIREK SOPEK CEO sopek@makolab.com Europe: MakoLab SA, Demokratyczna 46, 93430 Lodz, Poland Phone: +48 600 814 537, www.makolab.com USA: Makolab USA Inc, 20 West University Ave, Gainesville, FL 32601 Phone: +1 551 226 5488 , www.makolab.com

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