PROJECT PROPOSAL FOR NIRAL THIRUVIZHA

1. Theme : Artificial Intelligence

2. Problem statement : In today's digital era, organizations struggle to

understand user behavior during web sessions to enhance user experience,
improve engagement, and increase conversions. By analyzing session data,
we can predict user actions, such as purchase intent, abandonment, or click
paths. However, existing solutions often lack accuracy and real-time
processing capabilities. This project aims to leverage web mining techniques
to provide actionable insights into user behavior, enabling businesses to
make data-driven decisions and optimize their websites effectively.

3. College Code & College Name : 3101 & Anand Institute of Higher Technology

4. Guide Name, Designation, Mobile No. & Email id :

Mrs. P. Hema , Asisistant Professor , 8220643231, Hemap.aids@aiht.ac.in

5. Student Team details:

Sl.No. Student Reg. Name of the Branch Mobile No. email id

No. Student

1 310121205044 S.Revathi B.TECH&IT 960098929 padhmareshm

2 a
23@gmail.co
m
2 310121205019 S.Jeevitha B.TECH&IT 638322307 jeevithas590
9 @g
mail.com
3 310121205006 A.Deepika B.TECH&IT 741806440 d77486074@
1 g
mail.com

6. Project Summary: This project focuses on predicting user behavior through

session-based web mining. By processing and analyzing user interaction data
from web sessions, the system will identify patterns and trends to predict
future user actions. The proposed platform will include data preprocessing,
session segmentation, feature extraction, and behavior prediction using
machine learning models. This system will help businesses optimize their
websites and enhance user engagement.
7. Proposed solution with methodology :

Solution:

1. Session Segmentation: Identify and segment web session data to group user
interactions.
2. Feature Engineering: Extract key features from session data, such as
clickstream patterns, page visit duration, and navigation sequences.
3. Behavior Prediction: Use machine learning algorithms to predict user actions,
such as purchases or exits, based on session data.
4. Visualization and Insights: Provide dashboards for businesses to visualize user
behavior patterns and actionable recommendations.

Methodology:

1. Requirements Gathering: Understand business requirements and define the

scope.
2. Data Collection: Gather session data from websites using web tracking tools or
APIs.
3. Data Preprocessing: Clean and preprocess the data for analysis.
4. Model Development:. Develop machine learning models for behavior prediction.
5. System Deployment: Implement the solution as a web-based or cloud-based
application.

8. Workplan / time schedule indicating the project mile stone :

1. Planning and Analysis (1 week): Define objectives and gather requirements.

2. System Design (2 weeks): Design system architecture and user interface.
3. Data Collection and Preprocessing (3 weeks): Collect and clean session data.
4. Model Development (4 weeks): Build and train machine learning models.
5. Frontend and Backend Development (4 weeks): Develop the web-based
application.
6. Testing and Quality Assurance (2 weeks): Test the system for
performance and accuracy.
7. Deployment and Maintenance (2 weeks): Deploy the system and ensure
smooth operation.
9. Plan of action of implementation :

 Database Setup
1. Design the MongoDB database schema based on the defined requirements.
2. Establish connections between the backend (Node.js/Express.js) and the
MongoDB database.
3. Define relationships between different data entities (users, session data,
and behavior predictions).

 Backend Development
1. Create RESTful API routes for user authentication and authorization.
2. Implement user management functionalities (registration, login, profile
updates).
3. Develop API routes for managing session data, including CRUD operations.
4. Integrate machine learning models to analyze session data and predict user
behavior.

 Frontend Development
1. Set up the React.js project structure with components and pages.
2. Implement responsive and user-friendly dashboards for viewing session
analytics and behavior predictions.
3. Develop interactive forms for inputting session data and managing user profiles.
4. Implement data visualization components to display session patterns,
predicted behaviors, and actionable insights.

 Integration with Machine Learning Models

1. Integrate machine learning models into the backend for predicting user
behavior.
2. Build API endpoints to process session data and return predictions.

 Testing and Quality Assurance

1. Test the application to ensure it meets the requirements and functions as
intended.
2. Conduct user acceptance testing and gather feedback to refine the platform.

 Deployment and Maintenance

1. Deploy the application and make it accessible to users.
2. Provide ongoing maintenance and updates to ensure the application remains
effective and relevant.
10. Plan of action of implementation :

 Database Setup
4. Design the MongoDB database schema based on the defined requirements.
5. Establish connections between the backend (Node.js/Express.js) and the
MongoDB database.
6. Define relationships between different data entities (users, session data,
and behavior predictions).

 Backend Development
5. Create RESTful API routes for user authentication and authorization.
6. Implement user management functionalities (registration, login, profile
updates).
7. Develop API routes for managing session data, including CRUD operations.
8. Integrate machine learning models to analyze session data and predict user
behavior.

 Frontend Development
5. Set up the React.js project structure with components and pages.
6. Implement responsive and user-friendly dashboards for viewing session
analytics and behavior predictions.
7. Develop interactive forms for inputting session data and managing user profiles.
8. Implement data visualization components to display session patterns,
predicted behaviors, and actionable insights.

 Integration with Machine Learning Models

3. Integrate machine learning models into the backend for predicting user
behavior.
4. Build API endpoints to process session data and return predictions.

 Testing and Quality Assurance

3. Test the application to ensure it meets the requirements and functions as
intended.
4. Conduct user acceptance testing and gather feedback to refine the platform.

 Deployment and Maintenance

3. Deploy the application and make it accessible to users.
4. Provide ongoing maintenance and updates to ensure the application remains
effective and relevant.
11. List of facilities available in the college to develop the prototype of the project :

The college provides various facilities to develop the prototype of the project.
Computer laboratories are equipped with modern computers and software,
ensuring smooth development and testing. Programming languages and tools
such as Node.js and React.js are readily available for backend and frontend
development. Additionally, database management systems like MongoDB are
provided for efficient storage and management of session data. High-speed
internet and network connectivity enable seamless research and collaboration.
Tools like GitHub and Trello are accessible for version control, task
management, and team collaboration, ensuring the project is developed
efficiently and meets the desired objectives.

12. Nature of Industry support for the project, (if any) : NIL

13. Total Cost : 35000/-

14. Details of Financial assistance required (Limited to Rs 10,000/-) :

For financial assistance, our project "Predicting User Behavior Through Sessions Web
Mining" requires funding for machine learning model development, data
processing infrastructure, hosting, and maintenance. Potential sources include
grants, crowdfunding, investors, or partnerships with technology-focused
organizations.

15. Expected outcomes / results :

A fully functional "Predicting User Behavior Through Sessions Web Mining" system
that analyzes session data, predicts user behavior, and provides actionable
insights to optimize user engagement and decision-making.
 UNDERTAKING

1. ALL the students are studying in final year engineering. All the students
are registered only once for this scheme.
2. The college will provide the basic infrastructure and other required
facilities to the students for timely completion of their projects.
3. The college assumes to undertake the financial and other management
responsibilities of the project. We are aware that the amount is to be
utilized only for the purpose sanctioned i.e. to meet the expenses for
developing the prototype and not for purchase of computer consumables,
stationaries, honorarium, overhead etc. Unutilised balance amount will be
returned back to the University after the time of completion of the project.

Name and Sign Name and Sign Name and Sign Name and Sign
of Student of Student of Student of Student
1 2 3 4

Signature of the Mentor Signature and seal of the principal