using solr to find the right person for the right job
TRANSCRIPT
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Using Solr to find the right person for the right job
MAY 2 0 11 L AURA KANG
THE LADDER S . COM
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Agenda
• Search at the Ladders • Current Projects
– Standardiza2on of search products – Recommenda2on service
• Suggested Candidates – Tes2ng Sessions – Challenges and Future Work
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TheLadders.com
• $100K+ job search and career management • Right person for the right job, right job for the right person • > 4 million members
• Recruit Ladder • Community of recruiters and job seekers • Job search advisors and talent specialists
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Search at the Ladders
• January 2010: search team formed. – First member: computa2onal linguist, Dr. Leslie BarreD
• February 2011: plaYorm team formed. – 9 members – Search, CMS, shared services – Led by Ed Cudahy
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Solr/Lucene at the Ladders
Subscriber search
Candidate search
Recruiter search Job search Hiring
alerts search
Editorial content search
Search
Job to Candidate
Candidate to Job
Recruiter to Candidate
Sugges/ons
Recruiters like this
Candidates like this
Jobs like this
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Standardiza/on of Search Products
• Before – Legacy implementa2ons • Local Lucene index • Different versions of Solr
– Hard to make improvements
• Move to Solr 3.1.0
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Solr Setup
• Extended dismax • Preprocessing non-‐alphanumeric characters • Analyzers/Tokenizers
– Stop word removal – Index-‐side synonym expansion – Custom stemmers
• Custom length normaliza/on for job descrip/on and resumes • Replica/on • Mul/-‐core • Template: maven archetype • Autosuggest
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Challenges
• Power users – Large Boolean queries – Target result set of 50
• Synonyms with different lengths – HR manager vs. Human Resource manager – Phrase slop
• Company variants • Communica/ng to users
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Typical Query
• Title: "sales consultant" "sales engineer" "solu/ons architect" "solu/on architect" engineer architect
"pre-‐sales consultant" "presales consultant" "solu/ons engineer" -‐president -‐vp -‐cmo -‐ceo -‐cfo -‐chief -‐
director -‐so6ware -‐"s/w" –database
• Loca+on: Redwood City, CA, 100 miles
• Company: apple "ingram micro" "tech data" intermec "insight enterprises" "super micro computer" "digi
interna/onal inc" radisys "silicon graphics interna/onal corp" cray angilysys voltaire "concurrent
computer" gtsi "socket mobile" hp hewled hitachi ibm "i. b. m." "i.b.m." "interna/onal business
machines" "business machines" intevac xyratex quantum "western digital" wd w.d. ramtron "micron
technology" e.m.c. "e. m. c." sandisk brocade seagate 3par stec "dot hill" ocz o.c.z. "o. c. z." "hutchinson
technology" "hutchinson tech" lasercard edci dataram "overland storage" emc netapp
• Keyword: (presales "pre sales" pre-‐sales sales) AND (engineer engineering) AND (storage hardware "sun
microsystems" "sun servers")
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Recommenda/on Service
• RESTful web service • Solr backend • Tracking/feedback • A/B framework
Job to Candidate
Candidate to Job
Recruiter to Candidate
Recommenda/on Service
Recruiters like this
Candidates like this
Jobs like this
Client Applica/on
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Other Projects
• Resume parsing – Parse flagging
• Company list – Company variants – Similar companies
• Synonym list genera/on • Search help for users
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Suggested Candidates
• Coming soon on Recruit Ladder hdp://recruit.theladders.com • Suggest candidates that might be a good match when a recruiter posts a job • Goal:
– Help recruiters quickly iden2fy candidates that are right for the job – Increase interac2on between recruiters and job seekers
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Click to edit Master /tle style
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Click to edit Master /tle style
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Click to edit Master /tle style
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Suggested Candidates
• Hybrid – Categories
1. Posi/on level 2. Job special/es/disciplines 3. Industry • Job /tle => posi/on level (VP, director) + job func/on (marke/ng) • Relevance matrices for par/al matches
– Text • Job func/on keywords • Candidate’s job experience vs. job descrip/on using MoreLikeThis
• Boos/ng • Filters: salary range, years of experience, loca/on
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Challenges
• Cer/fica/ons and skills – Taxonomy
• “Good” resume – Resume scoring
• Job descrip/on – Short job descrip2ons – “Series 7 & 63 and 10+ years of experience in related field required” – Company descrip2on/Equal Employment Opportunity clauses
• Different priori/es for each job type
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Evalua/on
• Other products: – Mean-‐average precision: search – A/B tes2ng: suggested jobs
• Tes/ng sessions with talent specialists and external recruiters • Randomly selected set of jobs • Given 5 candidates and their resumes
0 = not a good match 1 = keep in pipeline 2 = contact
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Future Work
• Job descrip/on parser – Skills and cer2fica2ons
• UI improvements – Personalized weights and filters – Company descrip2on
• Geospa/al features • Recommenda/on Service: user ra/ngs • Search/Recommenda/on quality tes/ng framework
– Customer sa2sfac2on metrics – Pre-‐release metrics
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We’re hiring
• Email [email protected]
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Ques/ons?