By NizamUdDeen · · Reviewed by the Nizam SEO War Room editorial team.
First, the short version. Below is the AIO-eligible passage and the question-format primer for Information Retrieval Based on Historical Data.
First, read the definition above — it's the answer most search and AI engines extract first.
Second, scan the question-format H2s to find the specific facet you came for.
Third, follow the patent + related-entry links at the bottom to map the dependency graph around Information Retrieval Based on Historical Data.
What is Information Retrieval Based on Historical Data?
Patent overview Inventor Anurag Acharya, Matt Cutts, Jeff Dean, Paul Haahr, Monika Henzinger, others Assignee Google LLC Patent number US 7,346,839 Filing or grant year March 18, 2008 Patent family hi
Patent overview Inventor Anurag Acharya, Matt Cutts, Jeff Dean, Paul Haahr, Monika Henzinger, others Assignee Google LLC Patent number US 7,346,839 Filing or grant year March 18, 2008 Patent family hi
NizamUdDeen, Nizam SEO War Room
Patent overview
Inventor
Anurag Acharya, Matt Cutts, Jeff Dean, Paul Haahr, Monika Henzinger, others
Assignee
Google LLC
Patent number
US 7,346,839
Filing or grant year
March 18, 2008
Patent family
historical-data
Track
Monika Henzinger, Google Search Patents
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What this patent covers
98 search and IR patents by Monika Henzinger, the first Director of Research at Google. Co-inventor on the foundational near-duplicate-page-detection patent (US 6,138,113, with Dean) and an extensive set of document-scoring families (Query Analysis, Content Update, Inception Date, Link-Based Criteria, Historical Data — all cross-listed with Dean's canonical articles). Independent contributions: the detecting-duplicate-files family with William Pugh, the AltaVista connectivity-server, the connectivity-and-content-ranking patents, document-freshness determination, semantic-distance ranking, query-semantic-information ranking, anchor-text cross-language IR, in-context searching, hypertext-browser assistant, and usage-statistics-driven document retrieval. Spans 1997 to 2017.
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Why Information Retrieval Based on Historical Data matters
This patent is part of the Monika Henzinger, Google Search Patents research track inside the Nizam SEO War Room patents archive. It describes a piece of the search-engine machinery that working SEOs need to understand to optimize against modern ranking and retrieval systems. A deeper annotated walkthrough of this patent — covering the claims, the disclosure, the prior art it cites, and the algorithms it influences — is queued for the next archive expansion pass.
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Related research
Patents in the Monika Henzinger, Google Search Patents track are cross-linked to neighboring tracks where the same inventor or research lineage continues. Read this patent alongside the other entries in the track to recover the full research arc — the original disclosure, its continuations and divisional applications, and any follow-up patents that branched from the same line of work.
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For example, a working SEO consultant uses Information Retrieval Based on Historical Data when diagnosing a ranking drop, planning a content calendar, or briefing a client on why a tactic shifted. However, the concept only compounds when paired with the surrounding entries in the encyclopedia and patents archive. In addition, the platform connects this concept to live SERP data so the theory carries through to execution.
How does Information Retrieval Based on Historical Data work in modern search?
The full breakdown is in the article body above. In short: Information Retrieval Based on Historical Data ties into how search engines and AI answer engines weigh signals — every detail (definition, ranking impact, related patents, related signals) is captured in this article and cross-linked to neighboring entries in the encyclopedia and patents archive.
Working SEOs reach for Information Retrieval Based on Historical Data when diagnosing why a page ranks where it does, when planning a content strategy that aligns with the surfaces search engines and answer engines weigh, and when explaining ranking moves to non-technical stakeholders. The concept is one piece of the broader Semantic SEO + AEO operating system; the Nizam SEO War Room platform ties it to live SERP data, the patent lineage that introduced it, and the strategy moves that compound across projects.
Where Information Retrieval Based on Historical Data fits in the Semantic SEO + AEO stack
Search engines have moved from keyword matching toward semantic understanding, entity reasoning, and AI-mediated answer generation. Information Retrieval Based on Historical Data sits inside that shift — its weight, its measurement, and its downstream effects all changed when the underlying ranking and retrieval systems changed. Read the related encyclopedia entries linked above for the surrounding context.
The concept of Information Retrieval Based on Historical Data is grounded in the search-engine research lineage tracked in the Nizam SEO War Room platform. Primary sources:
Related encyclopedia entries and patent walkthroughs are linked inline above. The Strategy Brain inside the platform connects these sources to live project state so the research has a direct execution surface.
Finally, to summarize. Information Retrieval Based on Historical Data matters because it intersects directly with the signals search engines and AI answer engines use to rank and surface results. The full article above covers the mechanism in depth, the patents it derives from, and the related encyclopedia entries to read next.