InfiniteLoop-ProRecruiter

Result of CustomClassifier Model

Problem Identified

An average office worker receives 121 emails per day , spending 52% of their total work time on emails.
HR Recruiters juggle similar emails from numerous applicants. Switching between these different types of emails has productivity costs — a recruiter may add a new applicant to database, rearrange an interview, and cycle back to the previous task. Emails inform upcoming tasks to-do, but existing email filters do not classify based on specific content categories unless it is spam.

Solution Design

Batching similar tasks together saves time and reduces stress, much like an operating system reduces context switch overhead. As recruiters receive few standard formats of emails from applicants, what makes sense is an automated email classifier that leverages NLP to offload organisation work.

Implementation

Web-scraping to create dataset Select 30+ images of email examples per category to improve performance more than the minimal model requirement of 10 images. These are uploaded onto a S3 bucket.
Data Preparation Use AWS TextExtract to extract the email text body from images using and convert to required csv format. 5 labels { cold email, acceptance, rejection, follow up, interview acceptance } are assigned for supervised training data.
ML model AWS Comprehend CustomClassifier in multiclass mode labels emails as one of 5 classes. 10% of data is used for testing, which results in 85% model accuracy alt text
Deploy Using Amazon SNS to trigger AWS Lambda for classfication and email notification and through Outlook Rules, we redirect emails to pre-defined classification folders.

Future Development

Technical Improvements

Integrate with Amazon SES or WorkMail to generalise across email clients (constraint for setup during short hackathon duration) Allow client for customisation of categories

Extended Target Audience

Students: As individuals transitioning into the workforce, organizing professional and academic emails based on context provide clarity and categorization for productivity.

SME / Client-facing roles: For Start-up and SME Owners who play multiple roles and communicate with all stakeholders, organizing the channel of communication will save on time that's already short