Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering

Serendipitous Recommendation in E-Commerce Using Innovator-Based Collaborative Filtering is a project report that emphasizes the necessity of the recommendations in e-commerce applications. To distinguish the sharing of collaborative wisdom and experiences, collaborative filtering is of great help. The serendipitous recommendation is one of the algorithms suggested for innovative-based collaborative filtering. The balance between serendipity and accuracy is easily achievable. The recommendations in e-commerce can help in easy filtering that is mainly based on the innovator-based approach. The real data in eCommerce is easily collectible that can help in easy collaborative filtering using the serendipitous recommendations. The mini project report on serendipitous recommendation in e-commerce using innovator-based collaborative filtering is available. The users can free download abstract, synopsis on pdf to understand the effects of serendipitous recommendation in e-commerce using innovator-based collaborative filtering.

The necessary details related to how the serendipitous recommendation in e-commerce using innovator-based collaborative filtering is easily available through this report. The ppt-related to the same topic is also available here. The users can download on the report to understand the JAVA reports. It belongs to the JAVA reports category and available in word document. The way of managing the work related to the JAVA reports is easily available through this report.

This report emphasizes the importance of the project. The users can know easily about the serendipitous recommendation in e-commerce using innovator-based collaborative filtering by downloading the project. The report can enhance the way of using the serendipitous recommendation in e-commerce using innovator-based collaborative filtering. This can provide a complete overview related to the project.

Topics Covered:
01)Introduction
02)Objectives, ER Diagram
03)Flow Chats, Algorithms used
04)System Requirements
05)Project Screenshots
06)Conclusion, References