Semantic Search for Sourcing and Recruiting
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Semantic Search “The holy grail of search is to
understand what the user wants. Then you’re not matching words; you’re matching meaning.”
– Amit Singhal, Google
Can applications ever really know what we’re looking for?
Semantic Search Semantics: The study of meaning,
inherent at the levels of words, phrases, and sentences
Semantic Search: Searching beyond the literal lexical match and into the meaning of words, phrases, and sentences
5 Levels
Level 1: Conceptual1. Skill words/title association, variants,
and misspellings Director of business development,
business development director, etc. JDE, JD Edwards, etc. 10Q = SEC reporting SAP = ERP JMPC, JP Morgan, JPMorganChase
Level 1: How
Level 1 Semantic Search can be achieved through:
1. Man Application of knowledge of synonymous
terms and the relationships between concepts to search for variants and related terms
2. Machine Hierarchical or synonymous taxonomies Semantic Clustering
Level 2: Contextual2. Contextual
Words have different meaning depending on where they are specifically mentioned in resumes Summary, education, recent work
experience… Education vs. address (Harvard Ave.)
Level 2: How
Level 2 Semantic Search can be achieved through:
1. Man Innate understanding of contextual references Field-based search of parsed resumes/profiles
(most recent title, etc.)2. Machine
Parsing of resumes and profiles Automated field-based matching (most recent
exp., etc.)
Level 3: Grammatical3. Grammatical, natural language
search
Targeting sentence-level meaning with noun/verb combinations
Sentence-level semantics are much more powerful, predictive, and flexible than word or phrase level semantics
Level 3: ExamplesSearching for an identifying specific noun & verb combinations allows for the ability to target responsibilities and capabilities, not just keyword presence!
Examples of noun/verb combinations
"3 full life cycle SAP R/3 implementations"
"Carry out wound (pressure ulcer) assessment, recommend treatment…"
"SOX compliancy weekly internal auditing"
"Perform investment performance and attribution analysis"
Level 3: How
Level 3 Semantic Search can be achieved through:
1. Man Any search engine that supports fixed or
configurable proximity – the ability to control the distance between search terms
2. Machine No solution that I am aware of allows for the
automation of specifically targeting of noun/verb combinations to isolate sentence-level meaning
Level 3:Monster support* NEAR (CEO or CFO or CTO
or CIO or "C-Level" or chief*)
Level 3:Monster config* NEAR juniper NEAR router*
Level 3: Lucene
“created access database”~7
* PCRecruiter and some other ATS/CRM solutions use Lucene for text search/retrieval
Level 4: Inferential4. Implied skills, experience and responsibilities
Inferential semantic search is a form of Level 3 Talent Mining (Indirect search)
Inferential search involves specifically searching for what isn't explicitly mentioned – words and phrases that can imply experience that is not explicitly stated/present in a resume, LinkedIn profile, or other source of human capital data ▪ Infer: derive as a conclusion from facts or premises▪ Imply: to contain potentially, to express indirectly
Level 4: Inferential Text-based human capital data (e.g.,
resumes, LinkedIn profiles, etc.) is intrinsically limited and never provides a complete picture
People simply do not mention every detail about their professional career
Many talented people simply cannot be found via direct search methods, because their experience isn't explicitly mentioned anywhere If the text isn't present, it can't be retrieved!
Level 4: Example Let's say you need someone who has
managed EMC SAN projects/environments Realizing that some people will not
explicitly mention EMC or SAN (or any variant) in their resume/profile, you could search specifically for data center move, migration and consolidation experience, because this can imply SAN experience, and EMC is one of the largest SAN players*
* This isn't a theoretical example - I achieved a high level placement with a fantastic candidate at EMC using this exact approach!
Level 4: Example Let's say you need a Business Analyst with
PeopleSoft experience After exhausting all search methods using
"PeopleSoft" directly in queries, you could NOT out "PeopleSoft" and search for the mention of companies that you know use PeopleSoft
People who have worked at a company that is known to use PeopleSoft have a probability of experience with PeopleSoft, even in the absence of explicit mention of "PeopleSoft"*
* I filled a critical role at Sprint/Nextel using this exact method. The candidate had 3 recent and strong years of PeopleSoft project experience, and neither PeopleSoft nor any PeopleSoft related terminology was anywhere in her resume
Level 4: How
Level 4 Semantic Search can be achieved through:
1. Man Searching specifically for text that can imply skills
and experience that isn't explicitly mentioned 2. Machine
No solution that I am aware of allows for inferential semantic search beyond Level 1 conceptual search achieved through synonymous or hierarchical taxonomies (e.g., GAAP implies accounting exp.)
Level 5: Tagging
5. Human-reviewed and classified The highest level of semantic search involves
meaning applied by people and the ability to search for human capital data (resumes, social profiles, etc.) that has been identified, analyzed and labeled by a human
Searchable tagging allows the retrieval of human capital data that has been labeled after human analysis that can include information not actually present in the document/profile, as well as "intangibles" such as personality and cultural match
Level 5: How
Level 5 Semantic Search can be achieved through:
1. Man Tagging human capital documents, records
and profiles and the ability to search by tags 2. Machine
I'm not aware of any solution that has been developed to do this, but if I were to design one, it would involve the ability to automatically match across human-applied tags
Semantic CapabilitySemantic Search Human ApplicationLevel 1 - conceptual
YES YES
Level 2 - contextual
YES YES
Level 3 - grammatical
YES NO
Level 4 - inferential
YES NO
Level 5 - tagged YES NO?
Have a semantic search product? I'd be happy to evaluate it publicly or privately - Google me to contact
Thank You! Glen Cathey