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Towards a personalized Internet: a case for a full decentralization
1INRIA-Rennes Bretagne-Atlantique, France. anne-marie.kermarrec@inria.fr
Summary
Personalized search and notification systems can improve access to niche content online. Decentralized approaches are proposed to address scalability and privacy concerns in personalized information retrieval.
Area of Science:
- Computer Science
- Information Science
Background:
- The modern web is user-centric, with content sharing and social networking driving information exchange.
- Traditional search engines struggle to retrieve niche content due to their mass-market focus.
- Information overload and irrelevant notifications are significant challenges for users.
Purpose of the Study:
- To propose personalized search and notification systems for improved niche content retrieval.
- To advocate for implicit user interest capture over explicit classifications.
- To explore the benefits of decentralized systems for personalization.
Main Methods:
- Review of existing centralized personalization approaches.
- Argument for decentralized systems to enhance scalability and user privacy.
- Demonstration of personalization techniques within decentralized frameworks.
Main Results:
- Centralized personalization systems face scalability issues due to user-specific data storage.
- User reluctance to share personal data with large corporations is a growing concern.
- Decentralized systems offer a viable solution for scalable and privacy-preserving personalization.
Conclusions:
- Personalization is crucial for effective niche content discovery in the social web.
- Decentralized architectures are essential for future personalized search and notification systems.
- Further research is needed to advance decentralized personalization and its applications.
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