PEMS Method of expertise profiling – getting help

Automatic matching of candidates (WS: Work Seekers) or work opportunities (WP: Work Providers) requires profile input in 1) a structured format and 2) attributes that accurately capture human expertise. Instead of semantic search or Key Word search-based approaches, People Expertise Matching System (PEMS) method of expertise profiling is superior with large databases – in which there may be millions or hundreds of million records. PEMS can generate most relevant short-lists for WS or WP of work opportunities or candidates respectively. PEMS method can increase its effectiveness with some help for users – a Help Desk Executive or an AI Bot could provide this help. Bot can provide the help more smartly. This note describes the dialogue an AI Bot could conduct and help the user create accurate profile – for both WS and WP.
1. Occupation Title (OT) often does not adequately convey human expertise. A predefined list – linear or hierarchical of list of several thousand or even tens of thousands Occupation Titles is not good enough. Therefore, along with OT, it helps to capture Functional Areas of experience in a profile. Functional Area is a more meaningful and more granular attribute.
2. Functional Area is best defined with two components- Function (a verb) and Knowledge Domain (a noun). The pair of Function & Knowledge Domain defines a particular Functional Area.
3. As an example a user who is a Primary School Teacher (an OT) or wants to hire one, could be asked what are the best sets of Functions and Knowledge Domains that represent your expertise? She could answer – Function (a verb) is “Teach” and Knowledge Domains (nouns) are: Arithmetic, Geography, Science and English. To help the user provide the right inputs, AI Bot could ask – Specify the Function (s) you perform? And then for each Function, the Bot could ask – Specify one or more Knowledge Domains of your expertise.
4. Relevant Functions can be prompted after a web search and it may be noted that Functions at different levels of management hierarchy tend to follow a certain pattern:
  • Top Level functions usually include: Explore, Strategize, Research
  • Senior Level functions usually include: Plan, Design, Architect
  • Middle Level functions usually include: Control, Monitor
  • Junior Level functions usually include: Execute, Operate, Run
5. To recap, the PEMS method of expertise profiling dialogue for help explained stepwise:
Q1. Please specify your Occupation Title and Management Level?
Prompt: Examples of Occupation Titles are: Sales Manager, Specialty Nurse, Software Developer and CEO of a Steel Scaffolding Manufacturing Company. Examples of Management level and OTs are: Top Levels – CEO, CTO, CXO; Senior Levels – General Manager, Head of Marketing Department; Middle-level – Sales Manager, Production Manager, Production Supervisor; Junior Level – Machine Operator, Nurse in ICU; Truck Driver
Q2. After obtaining input of Occupation Title and Management Level, Bot may suggest relevant Functions (verbs) – searched from the web – and ask user to specify the relevant Functions s/he performs
Q3. After obtaining input of Functions, Bot may ask for Knowledge Domains of expertise for each Function; suggest relevant Knowledge Domains – searched from the web – also guide the user that for each Function, one can input multiple
Knowledge Domains Having got the above inputs, Bot may summarise the expertise (the OT, Management Level and list of Functional Areas of expertise) in the form of list and also a crisp description and seek confirmation of the user’s satisfaction with the description of the profile or make suitable corrections in previous inputs.