- Prof. Dr. Rupali M. Komatwar, Faculty, Computer Engineering, GPM.
In a world overwhelmed with information, finding precise and accurate answers efficiently is crucial. While doing research work, we often use resources like documents containing an abundance of lengthy information, official documentations, technical blogs, e-books, etc. to get a relevant answer for the questions from a particular data source. We, as learners, are usually recommended to read reference books for our academic subjects, which is good. However, there are times when we want quick and accurate answers. Even for that purpose, we have to thoroughly analyze the entire book which contains a bit of lengthy content. This work is very time-consuming, and it drains our energy in reading irrelevant information.
QueryMate is a tool that centers on developing an intelligent Question and Answering (Q&A) System that draws strength from custom dataset, revolutionizing the way users access and comprehend information. By training our model on carefully curated data, we aim to develop a solution that can understand context, extract relevant information, and accurate responses to user queries. The motivation behind this project stems from the ever-growing challenge of efficiently navigating to find information quickly in the huge amount of data. In a world where information is abundant but not always easily accessible, our tool can streamline the process of finding accurate and relevant answers to queries. Traditional keyword-based searches often fall short when it comes to understanding delicate queries or providing concise and relevant answers. We are doing this project because it’s getting harder to find what we’re looking for in all the information available. Regular searches don’t always understand our questions well or give us the right answers. So, we’re creating a sophisticated yet smart Q&A Tool using a special set of data to help fix this problem. Our project aims to bridge this gap by embracing the latest advancements in AI and NLP. Students and Learners can utilize this tool to get technical answers from their reference books. General users can save time by just doing a simple copy-paste and getting their query resolved. This will also help the Analysts and Researchers to get their insights from their data.
Week 01 : [31.07.2023 - 06.08.2023]
🚀 TEAM FORMATION AND MENTOR SELECTION
- Formation of our team, carefully assembling a group of dedicated members.
- After a series of collaborative meetings with the team, we carefully pinpoint our field and technology of interest.
- Selecting the mentor whose expertise aligns seamlessly with the chosen technology, ensuring the provision of the best guidance and support.
Week 02 : [07.08.2023 - 13.08.2023]
💬 PROJECT IDEA DISCUSSION AND DRAFTING OF SYNOPSIS
- Every team member has explored and actively contributed in examining and suggesting different project ideas.
- We settled on five project ideas before presenting them to our project mentor, Rupali ma'am.
- In a meeting, we presented our ideas to Rupali ma'am. She approved three out of the five ideas, providing us with explanations for selecting these three and her reasons for disapproving the other two.
- In the end, we opted for QueryMate because we deemed it more practical, useful and valuable.
Week 03 : [07.08.2023 - 13.08.2023]
🔍 EXPLORING PROJECT REQUIREMENTS
- We conducted a thorough review of prior work in this related field, if any has been undertaken.
- We began identifying and selecting further objectives that have the potential to greatly enhance the existing project's overall value and impact.
- We found it imperative to acquire datasets for training our models, enabling us to accurately predict the desired outputs.
- We agreed on utilizing
Google BERT (Bidirectional Encoder Representations from Transformers)andGoogle USE (Universal Sentence Encoder), while also considering the need forFacebook RoBERTa (Robustly Optimized BERT Pre-Training Approach)if any challenges arise withGoogle BERT - Taking into account the team's proficiency, we selected the following deep learning technologies:
NLP (Natural Language Processing)techniques, includingRNN (Recurrent Neural Networks)andLSTM (Long Short Term Memory)TensorFlowframework for robust model training.
- Overall, we chosed the technology stack for both the frontend and the backend of the project, with the committment to concurrently learn and master these technologies during the developmental phase:
- Frontend:
ReactJS - Backend:
NodeJS
- Frontend:
Week 04 : [14.08.2023 - 20.08.2023]
🔐 FINALIZING PROJECT PLAN
- We reviewed and confirmed the project requirements gathered during the previous week.
- We ensured that we had a comprehensive understanding of what needs to be accomplished.
- Alongside, we crafted a detailed project plan including milestones, deadlines and resource allocation.
- We organized regular team meetings to discuss progress, address any questions or concerns, and make any necessary adjustments to the project plan.
- Established the GitHub Repository for QueryMate on 15th August, 2023! ⭐
Week 05 : [21.08.2023 - 27.08.2023]
🛠️ SET UP THE DEVELOPMENT ENVIRONMENT
- We began by configuring our development environment, which involves setting up necessary software tools, version control systems, and ensuring that all team members have access to the required resources.
- Documenting our project is essential. Thus, we created a comprehensive initial project documentation that will encompass everything from project scope and requirements to technical specifications.
Week 06 : [28.08.2023 - 03.09.2023]
🎨 DEVELOPMENT KICK-OFF BY DESIGNING USER INTERFACE AND WIREFRAMES
- We dedicated our time for designing the system architecture, user interface (UI) and creating wireframes that outline the visual structure and flow of application.
- This included crafting visually appealing and user-friendly layouts, color schemes, and interactive elements that enhance the overall user experience.
- Additionally, we meticukously created wireframes, which are detailed blueprints of the user interface. These wireframes will serve as the visual foundation for our application, helping us plan the arrangement of elements and userflow.
- Throughout this week, we encouraged iterative design and feedback from team members to ensure that the UI aligns with project goals and user expectations.
- Now, we have a well-thought-out design before we start coding.
Week 07 : [04.09.2023 - 10.09.2023]
🧪 DEVELOPMENT AND TESTING
- With the project plan in place, we were ready to start the development process by implementing core project features.
- We began by setting up our development environment as planned during Week 5.
- Alongside development, we established a robust testing strategy to focus on thorough testing, including unit tests, integration tests, and user testing.
- Monitored development progress against the project plan, ensuring that we're on track and making necessary adjustments.