BlogBee’s news feed is a scrollable application where content will come one after another - that is as a list with content preview. If any user searches for a specific topic, the searching result will be shown as a grid content preview (like YouTube ). When anyone clicks on a particular content’s preview, then the whole document will be displayed. While reading a particular content/blog, similar types of content (based on the topics) will be recommended to the user. Any user can be able to search content, read content, and get recommendations for similar topic-related content. Registered users will also be able to save blogs, share, and react to each article. We are thinking about those social media or application users who are more comfortable reading the blog or textual content rather than watching videos. Our main goal is to make such an application that easily interacts with the user and provides a sufficient number of blog content that is initially fetched from youtube videos.

1. Software Project Lab II
Project Name: Blog Bee

2. BlogBee
Presented By
Md. Rakib Trofder
BSSE-1129
Md. Muktar Hosen
BSSE-1116
Supervised By:
Kishan Kumar Ganguly
Assistant Professor
Institute of Information
Technology
University of Dhaka
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3. Overview of BlogBee
BlogBee is a blog based social media where we can read
blog with others. Those blogs are auto generated from
youtube videos, our application provide item based
recommendations and classify blog.
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4. Item based Recommendation
● Collecting real data from user to rate blogs
● Convert to CSR (Compressed Sparse Row) Matrix
● Cosine similarity for this matrix
● Implement K Nearest Neighbors
● Find out appropriate blogs that are best suitable for
specific user
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5. Blog Classification
● Fetch Data from Sklearn Dataset to train
the algorithm
● CountVectorizer
● TF IDF Transformer
● Stochastic Gradient Descent Classifier
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6. Miscellaneous
● Video to Text Conversion
● Auto Updating user rating dataset when user rate on
blog and then recommended according to updated
dataset
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7. Quality Function Deployment
Normal requirements
◦ Web-Based Application
◦ Display Blog content from Youtube Videos
◦ Recommendation of contents according to user's previous
search
◦ Adding Blogs in favorite list
◦ Rating System
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8. Quality Function Deployment
Expected requirements
◦ Simple and user-friendly interface
◦ Authentication system
◦ Privacy on user information
◦ User History
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9. Quality Function Deployment
Exciting requirements
◦ Auto-tagging of contents
◦ User rating based on real-time recommendation
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10. Roadmap
10
1 3 5
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4
2
Youtube to Blog
Conversion Building Front
End
Item Based
Recommendation
Text
Classification
Collecting User
Data
Auto Updating
Recommendation
using data

11. Thank You