Developing a Chatbot for Employee Management

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MOHAMMED UMAR

I am a computer science engineering graduate, who passed out in 2021. I have been in the IT industry for the past year. I am working largely as a data engineer; my work includes developing data frameworks/pipelines mainly using Azure Data Factory and Google Data Flows and also developing data warehouses, I have experience using SQL servers and BigQuery. I also happen to work on the Business Intelligence side with having adequate experience with Power BI, Google Data Studio, and Tableau. I am proficient with python, and SQL and have experience working with REST APIs. I am currently working with Brio Technologies, we have partnerships with Microsoft, Google, and Amazon.

Ever since I have been in the Data Science program with Great Learning, I wanted to apply my skills in Machine learning and I got the opportunity from Brio, I was given the opportunity to make a chatbot for employee management. The tasks associated with this chatbot will be to

  • Help employees to log in/log out with simple commands.
  • To apply for leave easily.
  • To get access to their attendance logs.
  • To get their pay slips.

The structure of this chat bot consists of two main models:

  • One to classify the intent (what the user wants such as a leave or pay slip).
  • The other to classify the entities (when does the user want to leave and what type of leave is it going to be)

To classify the intents, I have used Neural Networks from the PyTorch module. For training purposes, we have made a JSON file with set intents, requests and responses and trained the model with the data.

To classify entities, I used the spacy module which under the hood uses multi-layer convolutional neural networks. To train the entities, we used a custom annotator to label the entities with their respective title.

We hosted the entire algorithm as a web API, and it responds to requests in the following way:

The chatbot will help approx. 200 employees working in my organization to have an easy way to undergo various tasks which will save their time and efforts immensely and also reduce HR operations workload by 15%. I want to extend my gratitude towards Brio Technologies for giving me this opportunity and also to Great Learning.

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