Daniel Scale, Structure, and Semantics
Daniel Tunkelang Principal Data Scientist at LinkedIn Recruiting Solutions 1

Take-Aways Communication trumps knowledge representation.
Communication is the problem and the solution. 2

Overview 1. Knowledge representation is
overrated. 2. Computation is underrated. 3. We have a communication problem. 3

The Bad News 1. Knowledge
representation is overrated. 2. Computation is underrated. 3. We have a communication problem. 4

AI: a dream deferred.
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Memex: the Computer Science Version
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Cyc
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Freebase
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Wolfram Alpha
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Knowledge representation is overrated. Today’s
knowledge repositories are: § incomplete § inconsistent § inscrutable § and not sustained by economic incentives. 1986 estimate of effort to complete Cyc: § 250,000 rules + 350 person-years 10

The Good News 1. Knowledge
representation is overrated. 2. Computation is underrated. 3. We have a communication problem. 11

Deep Blue
vs.
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Watson
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Plain Old Search Engines are
Pretty Good Too http://blog.stephenwolfram.com/2011/01/jeopardy-ibm-and-wolframalpha/ 14

The Unreasonable Effectiveness of Data
§ simple models + lots of data >> elaborate models + less data § machine translation: parallel corpora >> elaborate rules for syntactic and semantic patterns § semantic web formalism just means semantic interpretation on shorter strings between angle brackets Alon Halevy, Peter Norvig, and Fernando Pereira (2009) 15

Today’s Challenge 1. Knowledge representation
is overrated. 2. Computation is underrated. 3. We have a communication problem. 16

Semi-structured Data Michael K. Bergman,
http://www.mkbergman.com/ 17

Semi-structured Data at LinkedIn Summary
<person> I lead a data science <id> team at LinkedIn, which <first-name /> analyzes terabytes of <last-name /> data to produce products <location> and insights that serve <name> LinkedIn’s members. <country> Prior to LinkedIn, I led a <code> local search quality team </country> at Google and was a </location> founding employee of <industry> faceted search pioneer … Endeca (acquired by </person> Oracle in 2010), where…

Semi-structured Search is a Killer
App 19

Another Example: Helping a Friend
Dear Daniel, I'm attaching the resume of an old friend who just moved up to the Bay Area. He has a very strong background in: § mobile / wireless applications § start-ups and new product launches § international expansion Best regards, XXX 20

Company Search
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Semi-structured Data Empowers Users
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Data-Driven Recommendations
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Data-Driven Computation Serves Communication for
i in [1..n]! s ← w 1 w 2 … w i! if Pc(s) > 0! a ← new Segment()! a.segs ← {s}! a.prob ← Pc(s)! B[i] ← {a}! for j in [1..i-1]! for b in B[j]! s ← wj wj+1 … wi! if Pc(s) > 0! a ← new Segment()! a.segs ← b.segs U {s}! a.prob ← b.prob * Pc(s)! B[i] ← B[i] U {a}! sort B[i] by prob! truncate B[i] to size k! 24

Recommendations Leverage Semi-structured Data Job
Corpus Stats Matching Transition probabilities Connectivity Binary yrs of experience to reach title title industry … Exact matches: education needed for this title geo description … company functional area geo, industry, … User Base Soft Similarity (candidate expertise, job description) transition Filtered 0.56 probabilities, Similarity Candidate similarity, (candidate specialties, job description) … 0.2 Transition probability Text (candidate industry, job industry) General Current Position 0.43 expertise title specialties summary Title Similarity education tenure length 0.8 headline industry Similarity (headline, title) geo functional area experience … 0.7 . derive d . . 25

Skills: A Practical Knowledge Representation
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Data-Driven Query Expansion for Recall
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Data-Driven Query Refinement for Precision
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There is no perfect schema
or vocabulary. § And even if there were, not everyone would use it. § Knowledge representation has only succeeded within narrow scope. § Brute force is surprisingly effective but does not leverage the user as an intelligent partner. 29

Communication is the problem and
the solution. § Rich communication channel fills gaps in system’s knowledge representation and in user’s knowledge. § Use data science to make the system smart, but be humble and empower the human user. You've got the brawn I've got the brains Let's make lots of money Pet Shop Boys, “Opportunities” 30

The Future is Upon Us
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One More Thing “More data
beats clever algorithms but better data beats more data.” Monica Rogati @ Strata 2012 32

Thank You! Questions? Contact: dtunkelang@linkedin.com
We’re Hiring! 33