How RSSMonster Works

RSSMonster turns a stream of feed entries into an organized, prioritized, and personal reading experience. It combines deterministic article processing, source-level signals, semantic relationships, and each user’s reading behavior.

The major concepts build on one another:

Feeds and articles
        |
        +--> Feed scoring
        |
        +--> Article embeddings --> Events --> Topics
                                      |          |
                                      +----------+--> Interest Islands

Search expressions --------------------------------> Smart Folders

Key Concepts

Smart Folders

Smart Folders are saved, dynamic views powered by the same expressions used by RSSMonster search. New articles appear automatically when they match a folder’s query, without moving or copying the articles from their feeds.

Feed Scoring

Feed Scoring assigns a user-specific trust score to each feed. The score combines signals about the source and the user’s interactions to help prioritize useful material. It is separate from crawl reliability, article quality, and factual verification.

Article Embedding

Article Embedding represents an article’s meaning as a numeric vector. This lets RSSMonster compare articles semantically even when they use different words. Embeddings support recommendations and the semantic grouping layers; they do not alter or summarize the source article themselves.

Events

Events group articles that cover the same real-world occurrence. This reduces repeated coverage in the reading stream while keeping the different sources available. An Event answers: what happened?

Topics

Topics connect related Events into broader, recurring subjects. They persist beyond an individual story and answer: what ongoing subject does this belong to?

Interest Islands

Interest Islands form the private, user-specific personalization layer. They learn durable areas of interest from article relationships and reading signals such as clicks, bookmarks, and explicit feedback. An Interest Island answers: what does this user consistently care about?

Putting the Layers Together

RSSMonster first fetches and normalizes articles while preserving their identity and source. Feed and article signals help rank what should be shown. When semantic processing is enabled, article embeddings help associate reports with Events, connect Events to Topics, and relate that content to a user’s Interest Islands. Smart Folders provide a separate, deterministic way to build focused views using search rules.

Start with Concepts for the broader philosophy and terminology. For implementation-level details about the semantic pipeline, service boundaries, thresholds, and maintenance processes, see Semantic Services Implementation.

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