News aggregation gathers articles or feeds from publishers, normalizes their metadata, and organizes the material for discovery or further processing. An AI news product may then classify topics, identify related reports, summarize events, and link readers back to the sources.
Aggregation should preserve publication evidence and source attribution rather than presenting collected material as original reporting. Quality depends on source selection, update reliability, duplicate handling, date verification, and clear separation between source claims and generated interpretation.
ELI5
News aggregation brings reporting from several places into one organized view. It is like collecting newspapers onto one desk and sorting their stories by topic so readers do not need to search each source separately.
For example, a daily digest can collect trusted feeds, group articles about the same event, write a short overview, and provide links to the original reports. The links and dates let readers check where the information came from.
