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Month XX, 20XXPresented to [Client]-optional
Taxonomy at AOLClassifying the parts of a whole
Noel Agnew (@noelagnewny)Ashley Marty (@ashleykmarty)
June 09, 2011
The problem:
Aol did not have a common vocabulary
56+ Media brands, including:
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Multiple ad systems and content platformsContent platforms:BlogsmithHuffington Post (Movable type)5minTruveoStudioNow
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Some ad systems:AdTechAdvertising.comFeedpoint/Dynamic Banners
All speaking different languages…
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Tag.aol.com “beyonce”Tag… “beyonce knowles”AOL Music “beyonce”AOL music “beyonce knowles”Moviefone “beyonce knowles”Huffington Post “beyonce”H… Post “beyonce knowles”
What we were asked to doEffectively and granularly classify content: For improved ad sales To relate content within and between the brands In some cases, to assist editors with external-facing tags All sorts of other bits of magic (which will be touched on later)
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The solution:Classify all AOL content in the same way
Faceted Ontology
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“…structural frameworks for organizing information on the semantic Web and within semantic enterprises. They provide unique benefits in discovery, flexible access, and information integration due to their inherent connectedness; that is, their ability to represent conceptual relationships. ”
-M.K. Bergman, “An Executive Intro to Ontologies” http://www.mkbergman.com/900/an-executive-intro-to-ontologies/
SubjectsWe have approx. 6800 subjectsGenerally hierarchical, but some associative relationshipsIterative process with editors (subject specialists)
12 Top levels (or classes)
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Arts and HumanitiesEducationEntertainmentHealth and MedicineLifestyleMoney and Finance
News and PoliticsScience and TechSocial SciencesSportsTransportationTravel and Tourism
Entities
Named Things (includes persons)LocationsWorksEventsGroupsBrandsProducts
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Proper nouns (specific persons, places, things)Not hierarchical, but rather associative relationships
7 Entities Vocabularies
Taxonomy/ontology mashup
Technology
Electronics
Consumer Electronics
Smart Phones
Computing
Operating Systems
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iPhone
Apple
HTC Evo 4GOSX
AT&T
Verizon
Sprint
Making it work
HELLO TEL AVIV!When we were tasked with this, we had very little direct communication with the team in Tel Aviv that runs the classification engine…
We also were under the impression that auto-classification was their issue and they’d just have to classify with whatever we gave them. This was WRONG!
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Train in vain?
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‘Women's Shoes’We had to find training data for each subject in the taxonomy… and are continually doing so to improve classification.
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More Contact with the Classification TeamProviding Feedback on tagging resultsCollaborating on prioritiesWhat data is most valuable to the tagger?
Getting to Know You
Turning large amounts of data into an ontology
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Name: Beyoncé
More data sources means multiple records for the same Entity
After Merge, one record remains with metadata and relationships from all sources
More sources = More effort required in Merging records
More sources = More valuable records
MusicPersonMoviePersonAlias (synonym): Beyonce KnowlesAlias (synonym): BeyonceSource:WikipediaSource: AolMusicDBSource: AolMovieDB
Where we are now
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Integrating with Advertising systems
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Product Category Our SubjectBags, Wallets and Luggage > Laptop Bags > Laptop Cases Laptops
Bags, Wallets and Luggage > Luggage > Luggage Travel and Tourism
Home & Garden > Kitchen > Organization & Storage > Cookie Jars Cooking
Our subjects can be mapped to Advertising categories to serve ads for related products
Current Department Store campaign:
Recommending Tags for Editorial
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Where we’re going
On the Roadmap…More projects with Advertising teamsMore data in our ontology to make classification betterRefining the ontology- because it’s a living thing
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Lessons learned
Life lessons…Keep your eye on the prizeExpect people to think this is a much smaller task than it isDon’t reinvent the wheelNever underestimate the power of the ability to manipulate data
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