Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18775790 | ENTITY-RELATIONSHIP EMBEDDINGS | July 2024 | January 2026 | Allow | 18 | 1 | 0 | No | No |
| 18409687 | SYSTEMS AND METHODS FOR MACHINE LEARNING MODEL GENERATION | January 2024 | July 2025 | Allow | 18 | 3 | 0 | Yes | No |
| 17987874 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, NON-TRANSITORY COMPUTER READABLE MEDIA STORING PROGRAM, AND X-RAY ANALYSIS APPARATUS | November 2022 | December 2025 | Allow | 37 | 1 | 0 | No | No |
| 17949093 | METHOD AND APPARATUS FOR DISTRIBUTED AND COOPERATIVE COMPUTATION IN ARTIFICIAL NEURAL NETWORKS | September 2022 | January 2026 | Allow | 40 | 3 | 0 | No | No |
| 17819446 | SYSTEMS AND METHODS FOR FEW-SHOT NETWORK ANOMALY DETECTION VIA CROSS-NETWORK META-LEARNING | August 2022 | January 2026 | Allow | 42 | 1 | 0 | No | No |
| 17772925 | METHOD FOR RECOMMENDING INFORMATION, RECOMMENDATION SERVER, AND STORAGE MEDIUM | April 2022 | January 2026 | Allow | 45 | 1 | 0 | No | No |
| 17696380 | COMPUTERIZED SYSTEMS AND METHODS FOR USER ACTION PREDICTION | March 2022 | October 2025 | Allow | 43 | 1 | 0 | No | No |
| 17643050 | MACHINE LEARNING TECHNIQUES FOR ENHANCED REDIRECTION RECOMMENDATION USING REAL-TIME ADJUSTMENT | December 2021 | January 2026 | Allow | 50 | 3 | 0 | Yes | No |
| 17450134 | ATTENUATION WEIGHT TRACKING IN GRAPH NEURAL NETWORKS | October 2021 | July 2025 | Allow | 45 | 1 | 0 | No | No |
| 17486770 | AUTOMATIC DISCOVERY OF MACHINE LEARNING MODEL FEATURES | September 2021 | December 2025 | Allow | 51 | 1 | 0 | No | No |
| 17442987 | NEUROMORPHIC PROCESSOR AND NEUROMORPHIC PROCESSING METHOD | September 2021 | December 2025 | Allow | 51 | 1 | 0 | No | No |
| 17471816 | MERGING MODELS ON AN EDGE SERVER | September 2021 | October 2025 | Allow | 49 | 1 | 0 | No | No |
| 17465849 | CALCULATOR, DEEP LEARNING METHOD AND COMPUTER-READABLE RECORDING MEDIUM STORING PROGRAM FOR DEEP LEARNING | September 2021 | July 2025 | Allow | 46 | 1 | 0 | No | No |
| 17289626 | DEEP NEURAL NETWORK OPERATION METHOD AND APPARATUS | April 2021 | October 2025 | Allow | 54 | 1 | 0 | No | No |
| 11396836 | METHOD AND APPARATUS FOR LEARNING DATA, METHOD AND APPARATUS FOR GENERATING DATA, AND COMPUTER PROGRAM | April 2006 | September 2007 | Allow | 17 | 1 | 0 | No | No |
| 11319992 | CONTINGENCY TABLE ESTIMATION VIA SKETCHES | December 2005 | January 2009 | Allow | 36 | 4 | 0 | Yes | No |
| 11296020 | BUILDING PLANS FOR HOUSEHOLD TASKS FROM DISTRIBUTED KNOWLEDGE | December 2005 | December 2007 | Allow | 24 | 2 | 0 | No | No |
| 11188058 | METHODS, APPARATUS, AND DATA STRUCTURES FOR ANNOTATING A DATABASE DESIGN SCHEMA AND/OR INDEXING ANNOTATIONS | July 2005 | January 2009 | Allow | 41 | 2 | 0 | Yes | No |
No appeal data available for this record. This may indicate that no appeals have been filed or decided for applications in this dataset.
Examiner LO, ANN J works in Art Unit 2159 and has examined 11 patent applications in our dataset. With an allowance rate of 100.0%, this examiner allows applications at a higher rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 46 months.
Examiner LO, ANN J's allowance rate of 100.0% places them in the 94% percentile among all USPTO examiners. This examiner is more likely to allow applications than most examiners at the USPTO.
On average, applications examined by LO, ANN J receive 1.64 office actions before reaching final disposition. This places the examiner in the 32% percentile for office actions issued. This examiner issues fewer office actions than average, which may indicate efficient prosecution or a more lenient examination style.
The median time to disposition (half-life) for applications examined by LO, ANN J is 46 months. This places the examiner in the 11% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +0.0% benefit to allowance rate for applications examined by LO, ANN J. This interview benefit is in the 13% percentile among all examiners. Note: Interviews show limited statistical benefit with this examiner compared to others, though they may still be valuable for clarifying issues.
When applicants file an RCE with this examiner, 33.3% of applications are subsequently allowed. This success rate is in the 72% percentile among all examiners. Strategic Insight: RCEs show above-average effectiveness with this examiner. Consider whether your amendments or new arguments are strong enough to warrant an RCE versus filing a continuation.
This examiner enters after-final amendments leading to allowance in 50.0% of cases where such amendments are filed. This entry rate is in the 75% percentile among all examiners. Strategic Recommendation: This examiner shows above-average receptiveness to after-final amendments. If your amendments clearly overcome the rejections and do not raise new issues, consider filing after-final amendments before resorting to an RCE.
Examiner's Amendments: This examiner makes examiner's amendments in 9.1% of allowed cases (in the 92% percentile). Per MPEP § 1302.04, examiner's amendments are used to place applications in condition for allowance when only minor changes are needed. This examiner frequently uses this tool compared to other examiners, indicating a cooperative approach to getting applications allowed. Strategic Insight: If you are close to allowance but minor claim amendments are needed, this examiner may be willing to make an examiner's amendment rather than requiring another round of prosecution.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 12% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.