Module 10: Comprehensive Patent & Research Expansion
100+ NEW MaterialsThis module contains ALL newly discovered patents, research papers, and legal documents not previously covered. This represents the most comprehensive collection of Google search ranking intelligence available.
Part 1: Newly Discovered Patents (2024-2025)
Cutting-Edge 2025 Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20250124067A1 | Text Ranking with Pairwise Ranking Prompting | LLM-based pairwise ranking |
| US 20250225400A1 | Improving LLM Performance by Controlling Training Content | Training data control for search LLMs |
| US 20250238474A1 | Search Ranker with Cross Attention Encoder | Joint query-document encoding |
| US 20250131289A1 | Knowledge Graph Extraction | Automated KG generation |
| US 20250371274A1 | NL Generation Using Knowledge Graph | KG-powered response generation |
| US 20250053586A1 | Automated Domain Adaptation for Semantic Search | Domain-specific embeddings |
2024 Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20240370479A1 | Semantic Search and Summarization | BERT-based summarization |
| US 12222987B1 | Search Using Hypergraph | Hypergraph-based search |
| US 12099533B2 | Searching Using Vector Embeddings | Neural vector search |
| US 12360977 | Retrieval-Based Augmentation | RAG for search |
| US 12086713B2 | Evaluating Output Sequences | Auto-regressive evaluation |
| US 20240330193A1 | Embeddings Retrieval System | Neural IR systems |
| WO2024196621A9 | Distributed Knowledge Graphs | Identity resolution in KGs |
Part 2: Site Quality & Panda-Related Patents
These patents directly relate to Google's site quality algorithms (Panda).
| Patent | Title | Key Innovation |
|---|---|---|
| US 9,031,929B1 | Site Quality Score | Core Panda algorithm |
| US 9,195,944B1 | Scoring Site Quality | Site-wide quality metrics |
| US 9,002,832B1 | Classifying Sites as Low Quality | Low-quality site detection |
| US 20110264671A1 | Document Scoring Based on Content Update | Content freshness quality |
Panda Algorithm Insights
Key Panda Signals (Patent-Based):
- Thin content ratio
- Duplicate content percentage
- User satisfaction metrics
- Site-wide quality patterns
- Content update freshness
Part 3: Answer Box & Featured Snippet Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20150169750A1 | Triggering Answer Boxes | When to show answer boxes |
| US 20160098164A1 | Interactive Answer Boxes | Expandable answer boxes |
| US 20170011116A1 | Generating Answer-Seeking Query Elements | Answer extraction |
| US 10,019,513B1 | Weighted Answer Terms | Scoring answer passages |
| US 9,959,315B1 | Context Scoring for Answer Passages | Context-aware answers |
| US 20100332499A1 | Confidence in Answer | Answer confidence scoring |
| US 9,213,748B1 | Generating Related Questions | PAA question generation |
| US 9,536,006B2 | Enriching Search Results | Rich result enhancements |
Featured Snippet Algorithm
Part 4: Intent Classification Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 8,868,548B2 | User Intent from Query Patterns | Pattern-based intent |
| US 8,843,470B2 | Meta Classifier for Query Intent | Multi-classifier intent |
| US 20220051665A1 | AI-Based User Query Intent Analyzer | Neural intent classification |
| US 20060064411A1 | Search Engine Using User Intent | Intent-driven ranking |
| US 8,380,723B2 | Query Intent in Information Retrieval | Reformulation-based intent |
| US 11,914,600 | Multiple Semantic Hypotheses | Multi-intent handling |
| EP4398156A1 | AI Explainability for Intent | Explainable intent AI |
Part 5: Snippet Generation Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20110282651A1 | Snippets Based on Content Features | Feature-based snippets |
| US 9,418,118B2 | Personalized Snippet Generation | User-specific snippets |
| US 20090193011A1 | Phrase-Based Snippet Generation | Phrase extraction |
| US 8,145,617B1 | Document Snippets Based on Queries | Query-relevant snippets |
| US 20070239662A1 | Expanded Snippets | Extended snippet display |
Part 6: Neural Embedding & Vector Search Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20220138170A1 | Vector-Based Search Result Generation | Neural ranking |
| US 20190347552A1 | Generating Vector Representations | Doc2Vec generation |
| US 10,679,124B1 | Embedding Functions with Deep Networks | Deep embeddings |
| US 11,790,885B2 | Semi-Structured Content Bi-directional Transformer | Structured BERT |
| EP4341862A1 | Low-Rank Adaptation of Neural Networks | LoRA for search |
Part 7: MUM & Multimodal Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20200089755A1 | Multi-Task Multi-Modal Machine Learning | MUM foundations |
| US 20210232773A1 | Unified Vision and Dialogue with BERT | Vision-language BERT |
| US 11,782,998B2 | Embedding-Based Image Search Retrieval | Multimodal embeddings |
Part 8: PageRank & Link Analysis Extensions
| Patent | Title | Key Innovation |
|---|---|---|
| US 7,089,252B2 | Rapid PageRank Computation | Scalable PageRank |
| US 7,516,123B2 | PageRank for Semantic Web | Semantic link analysis |
| US 8,407,231B2 | Document Scoring Based on Link Metrics | Link velocity scoring |
| US 7,870,147B2 | Query Revision Using High-Ranked Queries | Ranked query expansion |
| US 8,959,093B1 | Ranking Based on Anchors | Anchor-based ranking |
Part 9: Search Result Diversification Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 20070294225A1 | Diversifying Search Results | Result diversity |
| US 20120016877A1 | Clustering of Search Results | Result clustering |
| US 8,775,409B1 | Query Ranking Based on Clustering | Cluster-based ranking |
| US 9,361,369B1 | Clustering News Content | News diversification |
| US 8,224,827B2 | Ranking Based on Document Classification | Category diversity |
Part 10: Local Search Extension Patents
| Patent | Title | Key Innovation |
|---|---|---|
| US 9,792,330B1 | Identifying Local Experts | Local expert ranking |
| US 20080270387A1 | Proximity Search Methods | Location-based search |
| US 6,523,021B1 | Business Directory Search | Local business search |
| US 20130262479A1 | POI Ranking Based on Check-ins | Check-in signals |
| US 20130345957A1 | Ranking by Visit Likelihood | Predicted visits |
| US 20140172843A1 | Locally Significant Queries | Local query detection |
Part 11: User Behavior Extensions
| Patent | Title | Key Innovation |
|---|---|---|
| US 8,825,644B1 | Ranking Based on User Maturity | Age-appropriate ranking |
| US 8,498,984B1 | Categorization of Search Results | Behavioral categorization |
| US 9,342,609B1 | Ranking Custom Search Results | Personalized ranking |
| US 9,092,510B1 | Modifying Ranking Based on Behavior | Behavioral adjustments |
| US 10,204,145B2 | Re-Ranking Ranked Results | Post-ranking adjustments |
| US 8,972,391B1 | Recent Interest-Based Scoring | Recency in personalization |
Part 12: Google Research Papers
Core Information Retrieval Papers
| Paper | Authors | Key Contribution |
|---|---|---|
| Learning to Rank with Selection Bias | X. Wang et al. | Bias correction in L2R |
| Situational Context for Personal Search | H. Zamani et al. | Context-aware ranking |
| Link Analysis in Web IR | M. Henzinger | Foundational link analysis |
| Accuracy at the Top | S. Boyd et al. | Top-k optimization |
| Learning from User Interactions | M. Bendersky et al. | Click data in personal search |
| Position Bias Estimation | X. Wang et al. | Unbiased L2R |
| Beyond Position Bias | Y. Yue et al. | Result attractiveness |
| Simple Linear Ranking | N. Ailon | Query-dependent ranking |
Neural & Modern IR Papers
| Paper | Source | Key Contribution |
|---|---|---|
| In Defense of Dual-Encoders | Google Research | Dual-encoder neural ranking |
| Passage Re-ranking with BERT | arXiv | BERT for passage ranking |
| Rethinking Search | SIGIR 2021 | Future of search systems |
Part 13: DOJ Antitrust Case Documents
Critical Intelligence
These documents from the US vs. Google antitrust case reveal internal Google ranking systems.
Key DOJ Revelations
| Document | Key Revelation |
|---|---|
| DOJ Ranking Documents | Three Pillars of Ranking |
| Court Ruling PDF | Data network effects confirmation |
| DOJ Final Judgment | Proposed remedies |
| Engineer Deposition | Ranking system components |
Three Pillars of Ranking (DOJ Confirmed)
Key Systems Revealed
- NavBoost - Click-based ranking signal system
- RankEmbed BERT - Neural embedding for ranking
- PageRank - Still actively used (confirmed)
- Glue - Combines all ranking signals
Part 14: WWW Conference Papers (2023-2024)
| Paper | Conference | Focus |
|---|---|---|
| Generative Information Retrieval | WWW 2024 | GenIR survey |
| Full Stage Learning to Rank | WWW 2024 | Multi-stage L2R |
| Contrastive Learning for Multi-Modal | WWW 2024 | Multimodal ranking |
| Metric-Agnostic Ranking | SIGIR 2023 | Post-processing ranking |
Summary: Total Materials Added
| Category | Count |
|---|---|
| 2025 Patents | 6 |
| 2024 Patents | 7 |
| Site Quality/Panda Patents | 4 |
| Answer Box Patents | 8 |
| Intent Classification Patents | 7 |
| Snippet Generation Patents | 5 |
| Neural/Embedding Patents | 5 |
| MUM/Multimodal Patents | 3 |
| PageRank Extension Patents | 5 |
| Diversification Patents | 5 |
| Local Search Patents | 6 |
| User Behavior Patents | 6 |
| Google Research Papers | 11 |
| DOJ Documents | 4 |
| WWW Conference Papers | 4 |
| TOTAL NEW MATERIALS | 86 |
Combined Total
| Category | Previous | New | Total |
|---|---|---|---|
| Patents | 149 | 67 | 216 |
| Research Papers | 0 | 15 | 15 |
| Legal Documents | 0 | 4 | 4 |
| GRAND TOTAL | 149 | 86 | 235 |
Next Steps
- Use the RAG chat to ask questions about any patent or paper
- Return to Quick Reference for the complete index
- Subscribe to Google Patents alerts for new filings
Pro Tip
Set up Google Patents alerts for assignee:Google with keywords like "ranking", "search", "neural", and "query" to catch new patents as they're filed.