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Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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AI Based Personalized News Aggregator

Authors: 1Sri Lakshmi N, 2Ganesh Relli, 3Madicharla suma, 4Chandana Deepika, 5Kaza yuvvesh;

AI Based Personalized News Aggregator

Abstract

AI Based Personalized News Aggregator will develop the news aggregator application, based on GNNs and meta-learning techniques, to provide a customized feed of news to the user. The system will model relationships between users, articles of news, and all the different topics that might affect people’s preferences by using GNNs, thus being able to understand how to gain connections and preferences in news consumption. The meta-learning principle will be taken advantage of in such a way that it can quickly adapt to changing preferences from individual users with a minimum amount of training data. It leads to a dynamic, efficient, and user- centered news recommendation platform that constantly learns on the fly and improves from user interactions.

Keywords

Personalized News Feed, Graph Neural Networks, Meta-Learning, News Aggregator

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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