Contextual estimation of link information gain
Topics: AI (Deep Learning), Freshness, Information Gain, Probably in use, Ranking, Reranking, Scoring, Semantic Search, User Signals
Contextual estimation of link information gain involves identifying and ranking documents based on how much new information they provide compared to what a user has already seen. This helps users quickly find the most useful documents without redundancy. The process uses machine learning to score and prioritize documents based on the additional insights they offer.
- In the provided patent, techniques are described for determining the information gain score of documents based on their relevance to a user’s query or interests.
- This involves identifying sets of documents, determining which ones offer new information beyond what the user has already seen, and presenting them accordingly.
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Your advantages:
+ Full analysis of hundreds of well researched active Microsoft and Google patents and research paper.
+ Save a lot of time and get insights in just a few minutes, without having to spend hours analyzing the documents.
+ Get quick exclusive insights about how search engines and Google could work with easy to understand summaries and analysis.
+ All patents classified by topic for targeted research.
+ New patent summaries and analysis every week. Weekly notification via E-Mail
+ Use all 4 AI Research Tools to gain insights from all documents in the database, the Google API Leak, Antitrust trial documents, the whole google support documents, fundamental knowledge from worlds best SEO experts, Bill Slawskis fundamental research work for the industry, books about semantic search and more in seconds.
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