Recommendation system for B2C E-commerce in Pakistan
The internet has changed the way business is conducted in the 21st century. Most importantly it has changed the face and pace of business offering a dispensable opportunity to operate on digital platforms. Businesses find new sources of competitive advantage so they are increasingly adding ecommerce
2025-06-28 16:28:56 - Adil Khan
Recommendation system for B2C E-commerce in Pakistan
Project Area of Specialization Computer ScienceProject SummaryThe internet has changed the way business is conducted in the 21st century. Most importantly it has changed the face and pace of business offering a dispensable opportunity to operate on digital platforms. Businesses find new sources of competitive advantage so they are increasingly adding ecommerce channels. In this case we are creating an ecommerce store which is a business to consumer store with a recommender system that automatically recommends products to the customer depending upon his activity on our Advance Search Engine.
As the pandemic has passed people have understood that how you can buy things online without getting into hassle of going to the market to buy things. For B2C Ecommerce store different businesses can connect to our store and can sell their products on our store and the recommender system will benefit by recommending product which they are looking for and recommend a product with good consumer rating.
Project ObjectivesTo facilitate the users with recommendations for the products based on the similarities, furthermore objectives are as following:
- To design system Easy to use.
- To find relevant products.
- To search in a quick way with Recommendation system.
- To Suggest or recommend only relevant products.
We often talk about web based projects which passes through following different steps:
- Develop an overall model
- Build a features list
- Plan feature
- Design by feature
- Build by feature
We have used Feature Driven approach in our project because it gives us a very good understanding of the project’s scope and context. FDD uses documentation to communicate and uses a user-centric approach. As our project is a long term project so FDD works well with large-scale, long-term, or ongoing projects. The five, well-defined steps make it easier to make new features and come up to speed on the project very quickly. Breaks feature sets into smaller chunks and regular iterative releases, which makes it easier to track and fix coding errors, reduces risk, and allows you to make a quick turnaround to meet our FYP needs.
Hardware:
- Computer not less than core i5 3rd generation.
- Processor not less than 2 GHz and RAM not less than 8 GB DDR3.
Software:
- Visual Studio Code.
- Web Browser.
Recommendation system to assist users to finding the similar products recommender system works as a provider in finding relevant and related products making relevant suggestions to the users. These systems navigate the Data Set through Machine Learning algorithms to come up with relevant suggestions for users based either on their explicitly mentioned preferences or objective behaviors. It is therefore necessary to build high-quality product recommender systems for providing fine-tuned recommendations to users in a wide range of daily-life applications. In this regard, researchers and industry practitioners need to come forward and work on some of the prominent issues and challenges the area of recommender systems, which are being presented in this proposal.
Technical Details of Final DeliverableThis is a web based Recommendation system for B2C E-commerce. There are two main beneficiary of this project which are given below:
- Users
- Administrators
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 43400 | |||
| Domain | Equipment | 1 | 15000 | 15000 |
| Hosting | Equipment | 1 | 15000 | 15000 |
| Courses(Backend) | Equipment | 1 | 6000 | 6000 |
| courses(frontend) | Equipment | 1 | 7400 | 7400 |