Review on Personalized Activity Notification and Feedback

News Aggregator is a real-time, personalized news and placement update service specifically tailored for students. It will be extremely difficult to keep up with in this age of information with information relevant to employment opportunities and pertinent information without the precise solutions in a timely manner. It caters to an application required by a centralized system that offers educational and professional content, well-curated towards individual academic or career interests. The system uses the application of ML and NLP for behavior and preference analysis regarding individuals. Real-time updates are supported using a blend of RSS feeds and APIs, and user-based collaborative filtering makes the suggestions more accurate. Enhanced NLP approaches like topic modeling (LDA), sentiment analysis (LSTM), and summarization are employed for processing news stories and placement updates iteratively and hence enhancing the relevance over time. News Aggregator simplifies access to essential information, thus facilitating academic and professional growth of students with the personalized news feed and placement alerts on time to ready them for upcoming opportunities.

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Publication Details

Journal
Engineering and Technology Journal
Published
2025-04-12
DOI
https://doi.org/10.47191/etj/v10i04.03
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Review on Personalized Activity Notification and Feedback

E. Padmalatha, S. Sandya Sneha Sri, Mareddy Tanvi
Engineering and Technology Journal
Technology and Data Analysis
article

Review on Personalized Activity Notification and Feedback

E. Padmalatha, S. Sandya Sneha Sri, Mareddy Tanvi
article en

Abstract

News Aggregator is a real-time, personalized news and placement update service specifically tailored for students. It will be extremely difficult to keep up with in this age of information with information relevant to employment opportunities and pertinent information without the precise solutions in a timely manner. It caters to an application required by a centralized system that offers educational and professional content, well-curated towards individual academic or career interests. The system uses the application of ML and NLP for behavior and preference analysis regarding individuals. Real-time updates are supported using a blend of RSS feeds and APIs, and user-based collaborative filtering makes the suggestions more accurate. Enhanced NLP approaches like topic modeling (LDA), sentiment analysis (LSTM), and summarization are employed for processing news stories and placement updates iteratively and hence enhancing the relevance over time. News Aggregator simplifies access to essential information, thus facilitating academic and professional growth of students with the personalized news feed and placement alerts on time to ready them for upcoming opportunities.

Engineering and Technology JournalVol. 10(04)
Chaitanya Bharathi Institute of Technology (IN)
Openalex Percentile: Top 91%
Technology and Data Analysis
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