This document presents an online shopping site for clothing using e-commerce. It introduces online shopping and notes problems with traditional shopping like long distances, time consumption, and limited hours. The objectives are to provide product information and develop the site using the Apriori algorithm for recommendations and binary search for searching. It describes the modules, use cases, and design. In conclusion, online shopping allows buying anytime, anywhere with Internet access and provides more enjoyment and detail than traditional shopping.

1. Online Shopping :
A Web Based E-commerce Site
For Clothing
Presented by :
Dipa Giri(3153/070)
Rasbindra Bhattarai(3170/070)
Roshish K.C(3174/070)
Sabana Maharjan(3175/070)
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2. INTRODUCTION
 Shopping is one of the essential part of our daily life.
 We are using different types of shops to buy different kinds of things everyday.
 Online shopping is a form of electronic commerce which allows consumers to directly
buy goods or services from a seller over the Internet using a web browser.
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3. Problem Definition
The mostly use existing system is manual system.
Longer distance problem.
Time consumed.
Harder to find certain things in different shop.
Shop is not open for 24/7.
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4. Objective
To provide the information about the product.
To develop the online shopping site using Apriori algorithm for
recommendation and Binary search algorithm for searching.
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5. Literature reviews
 From the study of Pan (2007, p.5), the author cited from Engel, Blackwell and Miniard (1990), that defines
purchasing intention as a psychological process of decision-making.
 According to Pan (2007), "purchasing decision process" is when the relevant information is searched by the
consumers that are motivated by the fulfillment of demands according to personal experience and the external
environment; then after accumulating a certain amount of information, they begin to evaluate and consider; and
finally after comparison and judgment, they make the decision on certain products.
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6. Algorithm will be used
• Apriori algorithm for recommending items.
• Binary search items for searching items.
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7. Module description
• Master Maintenance : consists of information about the products and services
• Transactions : management of shopping cart
• Reporting: reports will be generated
• Recommendation: recommend the items based on related products
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8. Use Case Diagram
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9. Design
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10. Conclusion
 Able to buy any time, any place, anywhere in contact of Internet service.
 More enjoyable and easier than real-world shopping.
 Provide detail information about product.
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11. References
 J. S. Breese, D. Heckerman and C. Kadie, " Empirical analysis of predictive algorithms for collaborative
filtering," in In Proceedings of the Fourteenth Conference on Uncertainty in Artifical Intelligence, 1998.
 A. Fernandez and . A. D. Miyazaki, "“Consumer Perceptions of Privacy and Security Risks for Online
Shopping.”".The Journal of Consumer Affairs 35.1 : 27-44.
 E. . B. and . M. , "purchasing decision process," 1990.
 B. M. Sarwar, G. Karypis, . J. A. Konstan and J. Reid, " Item-based collaborative filtering recommendation
algorithms," in In Proceedings of the 10th International World Wide Web Conference, 285-295.
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12. Any questions
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