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Uploaded byAndraz Tori
SemWeb install-fest presentation
The document provides an overview of the Zemanta API, which processes text to extract semantic information like tags, categories, concepts, entities, and related articles and images. It analyzes natural language to identify meaningful data that can then be linked to external databases. The API aims to bridge human understandable text and computer-processable data through natural language processing and knowledge extraction techniques. It has a variety of uses including content discovery, automatic information delivery, and linking data across information networks.
SemWeb install-fest presentation
- 1. Building upon theZemanta API Andraz Tori, CTO [email_address] Twitter: andraz
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- 4. Examples, demos &use-cases
- 5. What does itdo?
- 6. A Stargate ComputerProcessable Data Human Understandable Text
- 7. Initial design Input:a chunk of text
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- 9. Avoid proprietary entityidentifiers or taxonomies
- 10. Standard response formats:JSON, XML, RDF/XML
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- 15. Related images Mostused Most interesting Most obvious
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- 17. „ Interesting“ tags Explicitely mentioned
- 18. What the textis about as a whole
- 19. What concepts werenot mentioned, but could be relevant (for SEO)
- 20. Categories Deep hirarchy(100k categories)
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- 22. Good for contentorganization, ad-targeting, etc
- 23. Categories example Branded"unfilmable", Watchmen - the cult graphic novel about a group of retired, flawed superheroes - has finally made it to the big screen. From the second the opening credits roll, it is clear Watchmen is not your typical superhero movie.
- 24. An ageing vigilante,The Comedian, is attacked in his high-rise apartment before being hurled 10 storeys to his death... in graphic slow motion. What follows is a two-and-three-quarter hour epic that centres on an outlawed group of deeply flawed former heroes as a Cold War Doomsday clock inches ever closer to midnight and nuclear apocalypse.
- 25. First published in12 parts by DC Comics in 1986, Watchmen was written by the British team of Alan Moore and illustrator Dave Gibbons.
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- 34. Categories example Branded"unfilmable", Watchmen - the cult graphic novel about a group of retired, flawed superheroes - has finally made it to the big screen. From the second the opening credits roll, it is clear Watchmen is not your typical superhero movie.
- 35. An ageing vigilante,The Comedian, is attacked in his high-rise apartment before being hurled 10 storeys to his death... in graphic slow motion. What follows is a two-and-three-quarter hour epic that centres on an outlawed group of deeply flawed former heroes as a Cold War Doomsday clock inches ever closer to midnight and nuclear apocalypse.
- 36. First published in12 parts by DC Comics in 1986, Watchmen was written by the British team of Alan Moore and illustrator Dave Gibbons.
- 37. Concepts and entitiesIdentify relevant concepts and entities
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Editor's Notes
- #6 Cross domain – we didn't start with financial or health domain and then expanded our algorithms, we started from day one with cross domain capabilities
- #8 Tags have no background meaning, they are not tied to any database and they are not normalized in any way. They are what you would expect of a human not caring for standardization or normalization to choose from For example text mentioning Apple, Android and Google might get iPhone as a tag And mobile web as a tag, even when it wasn't mentioned anywhere.
- #9 Tags have no background meaning, they are not tied to any database and they are not normalized in any way. They are what you would expect of a human not caring for standardization or normalization to choose from For example text mentioning Apple, Android and Google might get iPhone as a tag And mobile web as a tag, even when it wasn't mentioned anywhere.
- #13 Disambiguation is done using background knowledge, for example we differ between London the city in UK, London in Ohio or Texas and Jack London, the writer
- #16 We are big fans of Freebase and Linking Open Data project
- #36 Zigtag, Faviki, AdpativeBlue, Zemanta, Yahoo, Freebase
- #39 Disambiguation is done using background knowledge, for example we differ between London the city in UK, London in Ohio or Texas and Jack London, the writer