CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS
Techniques, systems, architectures, and methods for efficient and accurate intelligence gathering comprising extensions to Knowledge Modeling (KM) schema that allow for the capture of additional contextual parameters, allowing analysts to capture additional data and information capable of answering...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | Perry, Kari Jenson, Nicholas R Swenson, Nicholas M |
description | Techniques, systems, architectures, and methods for efficient and accurate intelligence gathering comprising extensions to Knowledge Modeling (KM) schema that allow for the capture of additional contextual parameters, allowing analysts to capture additional data and information capable of answering "Who, What, When, and Where" type questions with respect to an adversary's behavior and processes. |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2021027175A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2021027175A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2021027175A13</originalsourceid><addsrcrecordid>eNrjZNB19vcLcY0I0fX0cwsNdnVRAHL9ffzdIxXc_IMUvP38w31cXdxdFXz9XVx9gnkYWNMSc4pTeaE0N4Oym2uIs4duakF-fGpxQWJyal5qSXxosJGBkaGBkbmhuamjoTFxqgB2lyak</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS</title><source>esp@cenet</source><creator>Perry, Kari ; Jenson, Nicholas R ; Swenson, Nicholas M</creator><creatorcontrib>Perry, Kari ; Jenson, Nicholas R ; Swenson, Nicholas M</creatorcontrib><description>Techniques, systems, architectures, and methods for efficient and accurate intelligence gathering comprising extensions to Knowledge Modeling (KM) schema that allow for the capture of additional contextual parameters, allowing analysts to capture additional data and information capable of answering "Who, What, When, and Where" type questions with respect to an adversary's behavior and processes.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210128&DB=EPODOC&CC=US&NR=2021027175A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210128&DB=EPODOC&CC=US&NR=2021027175A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Perry, Kari</creatorcontrib><creatorcontrib>Jenson, Nicholas R</creatorcontrib><creatorcontrib>Swenson, Nicholas M</creatorcontrib><title>CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS</title><description>Techniques, systems, architectures, and methods for efficient and accurate intelligence gathering comprising extensions to Knowledge Modeling (KM) schema that allow for the capture of additional contextual parameters, allowing analysts to capture additional data and information capable of answering "Who, What, When, and Where" type questions with respect to an adversary's behavior and processes.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNB19vcLcY0I0fX0cwsNdnVRAHL9ffzdIxXc_IMUvP38w31cXdxdFXz9XVx9gnkYWNMSc4pTeaE0N4Oym2uIs4duakF-fGpxQWJyal5qSXxosJGBkaGBkbmhuamjoTFxqgB2lyak</recordid><startdate>20210128</startdate><enddate>20210128</enddate><creator>Perry, Kari</creator><creator>Jenson, Nicholas R</creator><creator>Swenson, Nicholas M</creator><scope>EVB</scope></search><sort><creationdate>20210128</creationdate><title>CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS</title><author>Perry, Kari ; Jenson, Nicholas R ; Swenson, Nicholas M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2021027175A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Perry, Kari</creatorcontrib><creatorcontrib>Jenson, Nicholas R</creatorcontrib><creatorcontrib>Swenson, Nicholas M</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Perry, Kari</au><au>Jenson, Nicholas R</au><au>Swenson, Nicholas M</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS</title><date>2021-01-28</date><risdate>2021</risdate><abstract>Techniques, systems, architectures, and methods for efficient and accurate intelligence gathering comprising extensions to Knowledge Modeling (KM) schema that allow for the capture of additional contextual parameters, allowing analysts to capture additional data and information capable of answering "Who, What, When, and Where" type questions with respect to an adversary's behavior and processes.</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | eng |
recordid | cdi_epo_espacenet_US2021027175A1 |
source | esp@cenet |
subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | CONTEXT-INFUSED ONTOLOGY FOR KNOWLEDGE MODELS |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-16T07%3A06%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Perry,%20Kari&rft.date=2021-01-28&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2021027175A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |