Skills, Reputation, and Search
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Transcript of Skills, Reputation, and Search
Skills, Reputation, and Search
Pete SkomorochPrincipal Data Scientist, LinkedIn
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Vision: Create Economic Opportunity for Every Professional
TimeLocation
©2012 LinkedIn Corporation. All Rights Reserved.
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LinkedIn: The Professional Profile of Record
200+MMembers 200M MemberProfiles
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LinkedIn Search: Connecting Talent with Opportunity
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Skills Correlated with the Job Title “Data Scientist”
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Skills Related to “Big Data”
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Information Retrieval
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Soul Retrieval
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Lucene on LinkedIn
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Lucene Endorsement Graph
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Solr on LinkedIn
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Solr Endorsement Graph
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Reputation: Building the Endorsement Graph
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Viral Growth: 1 Billion Endorsements in 5 Months
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How Did We Gather this Data?
1. Desire + Social Proof
2. Viral Loops + Network Effects
3. Data Foundation + Recommendation Algorithms
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1) Desire & Social Proof
A endorses
B
B notified
B “accepts” endorsement
B endorses
C
B endorses
D
Endorsement recommendations
Email NotificationNews Feed2) Viral Loops & Network Effects
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3) Data Foundation: Skills & Suggested Skills
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Data Foundation: LinkedIn Skills
Social Tagging Accelerates Adoption
Suggested endorsements
Skill recommendations
Skill marketing
©2012 LinkedIn Cororation. All Rights Reserved.
Virality only
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Outline
Skill discovery
Skill tagging
Skill recommendations
Suggested endorsements
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Skill Discovery: Unsupervised Topics from Profiles
Extract
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Topic Clustering & Phrase Sense Disambiguation
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Deduplication Signals from Mechanical Turk
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Sample Task for Mechanical Turk Workers
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Skill Phrase Deduplication
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Outline
Skill discovery
Skill tagging
Skill recommendations
Suggested endorsements
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Lead designer and engineer for the implementation of a user-centric, fully-configurable UI for data aggregation and reporting.Developed over 20 SaaS custom applications using Python, Javascript and RoR.
Tagging Skill Phrases
Tagging: Extract potential skill phrases from text
Standardize unambiguous phrase variants
JavaScript RoR SaaS Python
ror
rubyonrails
ruby on rails development
ruby rails
ruby on rail
Ruby on Rails
Document (ex: Profile)
Tokenization
Skills Tagger
Phrases
(up to 6 words)
Skills Classifier
Skills
(unordered)
Skills
(ranked by relevance)
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Outline
Skill discovery
Skill tagging
Skill recommendations
Suggested endorsements
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Skill Inference
How suggested/inferred skills work:
– The skill likelihood is a conditional model
– Probabilities are combined using a Naïve Bayes Classifier
If you are an engineer at Apple, you probably know about iPhone Development.
Profile
Extract attributes
- Company ID
- Title ID
- Groups ID
- Industry ID
- …
Skills Classifier
Skills
(ranked by likelihood)
Feature
Vectors
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Skill Recommendations for Your LinkedIn Profile
49% Conversion
4% Conversion
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Outline
Skill discovery
Skill tagging
Skill recommendations
Suggested endorsements
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Social Tagging via Skill Endorsements
Social Tagging Accelerates Adoption
Skill endorsements
Skill recommendations
Skill marketing
©2012 LinkedIn Cororation. All Rights Reserved.
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Data Amplifies Desire
1. Desire + Social Proof
2. Viral Loops + Network Effects
3. Data Catalyst + Recommendation Algorithms
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Over 58 Million Profiles are now Tagged with Skills
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All This Data Flows Back Into Our Lucene Index
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Helping us Connect Talent & Opportunity
TimeLocation
©2012 LinkedIn Corporation. All Rights Reserved.
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Questions?
We’re hiring: data.linkedin.com
@peteskomoroch
CONTACTPete Skomoroch@peteskomoroch
http://data.linkedin.com