Christopher Brian Mckinley

Array ( [id] => 13611991 [patent_doc_number] => 20180357545 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-12-13 [patent_title] => ARTIFICIAL CONNECTOMES [patent_app_type] => utility [patent_app_number] => 15/658382 [patent_app_country] => US [patent_app_date] => 2017-07-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 9587 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => 0 [patent_words_short_claim] => 220 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15658382 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13846331 [patent_doc_number] => 20190026650 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2019-01-24 [patent_title] => BOOTSTRAPPING MULTIPLE VARIETIES OF GROUND TRUTH FOR A COGNITIVE SYSTEM [patent_app_type] => utility [patent_app_number] => 15/658106 [patent_app_country] => US [patent_app_date] => 2017-07-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5712 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -11 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15658106 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 17309487 [patent_doc_number] => 11210605 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2021-12-28 [patent_title] => Dataset suitability check for machine learning [patent_app_type] => utility [patent_app_number] => 15/658005 [patent_app_country] => US [patent_app_date] => 2017-07-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 11 [patent_figures_cnt] => 19 [patent_no_of_words] => 8450 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 171 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15658005 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13846297 [patent_doc_number] => 20190026633 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2019-01-24 [patent_title] => POST-PROCESSOR FOR FACTOID ANSWER CONVERSIONS INTO STRUCTURED RELATIONS IN A KNOWLEDGE BASE [patent_app_type] => utility [patent_app_number] => 15/657936 [patent_app_country] => US [patent_app_date] => 2017-07-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7485 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 129 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15657936 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 19925291 [patent_doc_number] => 12299577 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2025-05-13 [patent_title] => Tensor processing using low precision format [patent_app_type] => utility [patent_app_number] => 15/624577 [patent_app_country] => US [patent_app_date] => 2017-06-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 4 [patent_figures_cnt] => 4 [patent_no_of_words] => 1872 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 213 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15624577 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 17469515 [patent_doc_number] => 11275994 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2022-03-15 [patent_title] => Unstructured key definitions for optimal performance [patent_app_type] => utility [patent_app_number] => 15/601647 [patent_app_country] => US [patent_app_date] => 2017-05-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 10 [patent_figures_cnt] => 13 [patent_no_of_words] => 15244 [patent_no_of_claims] => 21 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 105 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15601647 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13569809 [patent_doc_number] => 20180336452 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-11-22 [patent_title] => PREDICTING WILDFIRES ON THE BASIS OF BIOPHYSICAL INDICATORS AND SPATIOTEMPORAL PROPERTIES USING A LONG SHORT TERM MEMORY NETWORK [patent_app_type] => utility [patent_app_number] => 15/601739 [patent_app_country] => US [patent_app_date] => 2017-05-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8604 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 120 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15601739 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13569871 [patent_doc_number] => 20180336483 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-11-22 [patent_title] => SELF-OPTIMIZING INFERENTIAL-SENSING TECHNIQUE TO OPTIMIZE DEPLOYMENT OF SENSORS IN A COMPUTER SYSTEM [patent_app_type] => utility [patent_app_number] => 15/601766 [patent_app_country] => US [patent_app_date] => 2017-05-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7506 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 149 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15601766 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 12033112 [patent_doc_number] => 20170323211 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2017-11-09 [patent_title] => 'AUTOMATED ACCURACY ASSESSMENT IN TASKING SYSTEM' [patent_app_type] => utility [patent_app_number] => 15/588478 [patent_app_country] => US [patent_app_date] => 2017-05-05 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 15 [patent_figures_cnt] => 15 [patent_no_of_words] => 19773 [patent_no_of_claims] => 18 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15588478 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13483883 [patent_doc_number] => 20180293484 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-10-11 [patent_title] => INDICATING A RESPONDING VIRTUAL ASSISTANT FROM A PLURALITY OF VIRTUAL ASSISTANTS [patent_app_type] => utility [patent_app_number] => 15/484991 [patent_app_country] => US [patent_app_date] => 2017-04-11 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 17459 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 81 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15484991 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 11966263 [patent_doc_number] => 20170270416 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2017-09-21 [patent_title] => 'METHOD AND APPARATUS FOR BUILDING PREDICTION MODELS FROM CUSTOMER WEB LOGS' [patent_app_type] => utility [patent_app_number] => 15/459495 [patent_app_country] => US [patent_app_date] => 2017-03-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 7 [patent_figures_cnt] => 7 [patent_no_of_words] => 11048 [patent_no_of_claims] => 24 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15459495 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 13433515 [patent_doc_number] => 20180268300 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-09-20 [patent_title] => GENERATING NATURAL LANGUAGE ANSWERS AUTOMATICALLY [patent_app_type] => utility [patent_app_number] => 15/459134 [patent_app_country] => US [patent_app_date] => 2017-03-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 6642 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 225 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15459134 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 11958621 [patent_doc_number] => 20170262773 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2017-09-14 [patent_title] => 'METHOD AND SYSTEM FOR GENERATING A TRAINING MODEL FOR FABRICATING SYNTHETIC DATA AND FOR FABRICATING SYNTHETIC DATA' [patent_app_type] => utility [patent_app_number] => 15/455207 [patent_app_country] => US [patent_app_date] => 2017-03-10 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 27 [patent_figures_cnt] => 27 [patent_no_of_words] => 9053 [patent_no_of_claims] => 17 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15455207 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 11709503 [patent_doc_number] => 20170178003 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2017-06-22 [patent_title] => 'DATA PATTERN ANALYSIS USING OPTIMIZED DETERMINISTIC FINITE AUTOMATION' [patent_app_type] => utility [patent_app_number] => 15/445687 [patent_app_country] => US [patent_app_date] => 2017-02-28 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 13 [patent_figures_cnt] => 13 [patent_no_of_words] => 7669 [patent_no_of_claims] => 17 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15445687 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 14826231 [patent_doc_number] => 10410126 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2019-09-10 [patent_title] => Two-model recommender [patent_app_type] => utility [patent_app_number] => 15/400151 [patent_app_country] => US [patent_app_date] => 2017-01-06 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 4 [patent_figures_cnt] => 4 [patent_no_of_words] => 8343 [patent_no_of_claims] => 15 [patent_no_of_ind_claims] => 1 [patent_words_short_claim] => 308 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15400151 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 11494700 [patent_doc_number] => 20170068885 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2017-03-09 [patent_title] => 'DUAL DETERMINISTIC AND STOCHASTIC NEUROSYNAPTIC CORE CIRCUIT' [patent_app_type] => utility [patent_app_number] => 15/353675 [patent_app_country] => US [patent_app_date] => 2016-11-16 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 15 [patent_figures_cnt] => 15 [patent_no_of_words] => 8043 [patent_no_of_claims] => 12 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15353675 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16292669 [patent_doc_number] => 10769521 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2020-09-08 [patent_title] => Processing loops in computational graphs [patent_app_type] => utility [patent_app_number] => 15/346626 [patent_app_country] => US [patent_app_date] => 2016-11-08 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 9 [patent_figures_cnt] => 9 [patent_no_of_words] => 9304 [patent_no_of_claims] => 15 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 310 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15346626 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15473221 [patent_doc_number] => 10552488 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2020-02-04 [patent_title] => Social media user recommendation system and method [patent_app_type] => utility [patent_app_number] => 15/288567 [patent_app_country] => US [patent_app_date] => 2016-10-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 7 [patent_figures_cnt] => 8 [patent_no_of_words] => 6936 [patent_no_of_claims] => 18 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 448 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15288567 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 12121525 [patent_doc_number] => 20180005112 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2018-01-04 [patent_title] => 'ARTIFICIAL NEURAL NETWORK WITH SIDE INPUT FOR LANGUAGE MODELLING AND PREDICTION' [patent_app_type] => utility [patent_app_number] => 15/245934 [patent_app_country] => US [patent_app_date] => 2016-08-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 8 [patent_figures_cnt] => 8 [patent_no_of_words] => 8378 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 0 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15245934 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 14643165 [patent_doc_number] => 10366329 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2019-07-30 [patent_title] => System and method for addressing overfitting in a neural network [patent_app_type] => utility [patent_app_number] => 15/222870 [patent_app_country] => US [patent_app_date] => 2016-07-28 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 2 [patent_figures_cnt] => 2 [patent_no_of_words] => 2378 [patent_no_of_claims] => 19 [patent_no_of_ind_claims] => 2 [patent_words_short_claim] => 343 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15222870 [rel_patent_id] =>[rel_patent_doc_number] =>)