How Simple Search Works in RChilli's Search & Match API – RChilli HelpDesk

RChilli’s Simple Search functionality within the Search and Match API provides a streamlined and powerful method to locate candidates or jobs based on keywords, while still leveraging RChilli’s rich taxonomy and intelligent search engine.

What is Simple Search?

The Simple Search endpoint converts a user's plain text query into a structured, intelligent search by:

Tagging keywords with relevant entities such as skills, job titles, locations, experience, tools, and languages.
Utilizing Search & Match Engine 3.0 which applies taxonomy-based normalization, deduplication, and semantic search techniques to improve results.

Example:

If you search for: "Java developer in New York with 5 years experience"
The system will:

Recognize Java as a skill,
Identify developer as a job title,
Tag New York as a location,
Understand 5 years experience as a filter for work experience.

Core Functionalities of Simple Search

Keyword Interpretation
Simple Search parses the input string and enriches it with tags (like skills, tools, education, etc.) for deeper understanding.
Semantic Matching
It finds relevant candidates/jobs even if the exact keywords do not match. For example, if a resume says "Software Engineer," it can match with the query "Developer" using taxonomy mappings.
Faceting & Filtering
The output includes facets (metadata-based filters) like location, company, education level, skill set, etc., which can be used to refine search results.
Ranking & Scoring
Candidates or jobs are scored based on relevance using a dynamic scoring engine. Weights can be assigned to different attributes like skills, education, and domain.
Pagination & Bulk Handling
Search results are paginated for better performance and scalability. You can navigate through large sets of results with ease.

How It's Different from Advanced Search

While Advanced Search allows structured and filtered queries using field-specific parameters (e.g., location: New York, skill: Java), Simple Search offers:

Free-text input.
Automatic tagging and field detection.
Faster setup and usability for end-users.

Use Cases for Simple Search

Recruiters typing natural language queries to find best-fit candidates.
Job Boards providing simple keyword-based job/candidate search to users.
Chatbots that pass user-typed job preferences to the API for real-time suggestions.
ATS systems enhancing their built-in search without complex configurations.

Technical Resources

Benefits

Quick implementation with minimal setup.
Enhanced candidate discovery through AI.
Configurable scoring and filtering.
Scalable for large recruitment platforms.

If you have any questions, you can always contact RChilli support at support@rchilli.com.