What technology is used for identifying relevant and adjacent skills, and what is the baseline for skill extraction and matching?

RChilli's Technology for Skill Extraction & Matching

RChilli combines AI-driven parsing, Taxonomy 3.0, and dynamic scoring logic to extract, identify, and match relevant as well as adjacent skills with high precision. Here's how it works:

1. Taxonomy 3.0 Framework

RChilli’s Taxonomy 3.0 powers semantic skill extraction and enrichment, with:

• 3M+ Skills

• 2.4M+ Job Profiles

• Multilingual Support

• Government Database Alignment (USA, EU, Canada, Australia)

• Ontology Mapping of skills to job domains, tools, industries, and roles

This framework ensures relevance (direct skill match) and adjacency (related/synonymic skills) for deep, intelligent talent mapping.

Taxonomy API Overview
Taxonomy Usage in MyAccount

2. AI + Deep Learning + LLM Integration

RChilli’s Search & Match Engine 3.0 and Resume Parser are powered by:

• AI/ML models for parsing structured data

• Neural networks to understand job-role nuances

• LLMs (e.g., OpenAI GPT) for contextual awareness, synonym recognition, and implicit skill inference

This enables matching even when skills are not explicitly mentioned, by recognizing equivalents and related roles.

LLM Parsing - OPEN AI (Beta) Enhancement

LLM Parser - Azure OPEN AI (Beta) Enhancement

Baseline for Skill Extraction & Matching

A. Default Matching Logic

The built-in scoring model assigns standard weights to:

• Skills

• Location

• Education

• Domain

• Job Titles

Best suited for clients who don’t need extensive configuration.

Search & Match API Overview

B. Customizable Logic (Dynamic Weighting)

• Configure weightage directly from the UI

• Adjust factors like:

  • Skill priority

  • Location emphasis

  • Employer/industry relevance

Frontend configurations dynamically affect the backend scoring without modifying core logic.

Dynamic Scoring Configuration Guide
How Scoring Works in Search & Match

Skill Segregation & Experience Context

• SkillKeyword: Flat list of all extracted skills

• SkillSegregation: Enriched with:

  • Skill type (e.g., Soft, Technical)

  • Source section (e.g., Work, Education)

  • Experience duration, if available in Experience or Projects

Skill Grouping & Segregation Guide

Adjacent Skill Identification with Taxonomy API

To fetch comparable, related, or synonymic skills, use:

• RChilli Taxonomy API

  • Get abbreviations (e.g., PM for Project Manager)

  • Synonyms and job family expansions

  • Intelligent suggestions for related titles

Taxonomy Standardization Endpoint

Note: This feature requires explicit API calls and is not bundled by default in parsing or match endpoints.

Maintenance & Updates

• RChilli performs monthly taxonomy refreshes

  • Adds new skills and tools

  • Updates outdated terminology

  • Enhances multilingual and geo-compliant support

Taxonomy Refresh and Scoring Update Cycle

Summary

Need Help or a Demo?

• Email: support@rchilli.com

• Explore: RChilli Knowledge Center

• API Developer Docs