Abstract:
Today, millions of news sources are available online, making online news reading popular. Choose news by theme. Identifying topic-related news is essential. Author-driven news. This system greatly improves recommendation. Better user interaction can do this. It suggests relevant information with a balanced author-reader perspective to overcome traditional news proposal bias.
The topic patterns of the original news posting and its comments, one of the most useful social media user behavior records, are used to do this. Hidden topic patterns are extracted from comments’ textual and structural information to capture users’ dynamic concerns. Keywords from comments are compared to database keywords.
We model the relationship between comments and the original posting. Our solution recommends news well. This system will improve news recommendation by taking author and reader suggestions. This system’s news recommendation algorithm is different from traditional news proposal. This system will help web users find news articles by topic.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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