What is RSS Filter?
RSS Filter is an intelligent recommendation system designed to help you manage information overload from your RSS feeds. By leveraging large language model (LLM) embeddings and machine learning, it analyzes your reading habits and filters out noise, delivering only the articles that matter most to you. Simply replace your original RSS feed URLs with the filtered versions, and the system begins tracking which articles you read. Over time, it learns your preferences and reduces unwanted items, ensuring you never miss important content.
Key features include automatic feed conversion via OPML import—you can upload an export from your current RSS client to instantly apply filtering to all your feeds. The system uses state-of-the-art embeddings to understand article semantics and machine learning algorithms to recommend similar articles based on your past reads. This means the more you use it, the better it becomes at surfacing relevant content.
Benefits include saving time by cutting through clutter, discovering new articles aligned with your interests, and maintaining a manageable feed list. Use cases are ideal for professionals, researchers, or anyone overwhelmed by high-volume RSS subscriptions. Technical details: The tool is open-source and available at m0wer/rssfilter. It supports standard OPML format and works with any RSS reader that allows custom feed URLs. Feedback is welcome via email at m0wer (at) autistici (dot) org. Start filtering your feeds today and reclaim your reading time.
Use Cases
Key Features
OPML import LLM embeddings reading habit analysis noise filtering personalized recommendations automatic feed conversion semantic understanding machine learning algorithms time saving clutter reductionWho is it for?
professionals, researchers, content curators, journalists, knowledge workers, students, avid readers
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