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WordLift 2.0 presented on the Semantic Web Meetup in Rome

  1. THINGS STRINGS NOT by @cyberandy
  2. WORDLIFT 2.0 beta preview in partnership with:
  3. LANGUAGE Symbolic, USER information is stored in the form of a code or symbol Resides in the mind of people, NOT in STRINGS Governed by rules - understanding rules help us understand one another STRING THING (SYMBOL) (REFERENT)
  5. KNOWLEDGE GRAPH 1. Language becomes less ambiguous (FINDING) 2. Key facts are displayed along with the query (KNOWING) 3. Inter-relationship among “Things” brings the intelligence to the machine (UNDERSTANDING) 4. Reality unveils curiosities (DISCOVERING) SEARCH ENGINES UNDERSTAND...
  6. GOOGLE KNOWLEDGE GRAPH • Includes today more then 500 million things (~ 0.077 of people alive on earth) • It’s made of data from Freebase, Wikipedia, the CIA World Factbook and data publicly available on the Web •3.5 billion facts about and in relationship with these 500 million entities • It’s based on users’ search behaviors
  8. In a nutshell • Knowledge comes from many sources search engines - closed index • Search engines are building their Cast information knowledge graphs using web crawling from billion of web Attributes pages techniques • We want to do it with the help of Entity web editors providing: • an open knowledge base aemoo web - open knowledge base cast information from Blogger A • an aggregated and consistent views cast information of all entities Attributes from Blogger B Cast information • an intuitive classification ontology from open repository (DBPedia, Freebase) • a new way to browse the web of Entity objects
  9. Social WORDLIFT 2.0 Thing Media Ready Plot Summary (RSS/GEORSS/JSON) Company Truly Product engaging Creative Work Person Supporting Event How a Content Intensive web site can benefit from a semantic driven UI and a more structured content architecture Place
  10. Mission Statement • Empowering editors with new publishing tools and a federated platform for named entity sharing,  a suite of technologies to enable intuitive • Designing content discovery and recommendation using Semantic Web and the LOD Cloud, new means of information • Providing consumption for multiple languages, • Marketing web contents using “things”.
  11. Rome, Cairo, Tel Aviv Grazie! InSideOut10
  12. CREDITS this presentation is the result of many inspiring ideas and world-wide famous memes, here is the list: Amit Singhal, Engineer at Google - Amit_Singhal Michael Bergman, Semantic Expert - mike/ any idea, graphics or meme belonging to us is available for sharing, copying and re-mixing under creative commons license 3.0