Abstract
A method for stateful ranking of search results may be used to prioritize novel content when a user repeats a query, for example, for a developing news story. A system can establish a "context timestamp" based on a user's most recent prior query on a topic. The system may then identify "context results," which can be items published before this timestamp, and "latest results," which can be items published after it. To differentiate new information, the system may computationally compare the latest results to the context results, for instance, by generating vector embeddings and identifying latest results with a similarity score below a defined threshold. This process can be used to determine which results are potentially informationally novel, as opposed to only recently published. The identified novel results may then be algorithmically prioritized and promoted, which can assist in presenting a user with current developments in a story they are following.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Shah, Deep and Bhandari, Aditya, "Stateful News Ranking to Prioritize Novel Content for Repeat Queries", Technical Disclosure Commons, (October 27, 2025)
https://www.tdcommons.org/dpubs_series/8787