ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS

An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features usin...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	ALLOUCHE, Yair, BILLER, Ofer Haim, FARCHI, Eitan Daniel, COHEN, Aviad, ACKERMAN, Samuel Solomon
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
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	ALLOUCHE, Yair BILLER, Ofer Haim FARCHI, Eitan Daniel COHEN, Aviad ACKERMAN, Samuel Solomon
description	An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features using feature grouping. The processor can then detect an anomaly in response to detecting that an associated unbiased outlier score of the sample is higher than a predefined threshold.
format	Patent
fullrecord	<record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2024176784A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2024176784A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2024176784A13</originalsourceid><addsrcrecordid>eNrjZDB1dHEMCPEMc_WJVHB39XMNcgzx9HNX8A8N8fF0DVIIdvYPcg1WCA0GCXp4Bof4uwc5-gbzMLCmJeYUp_JCaW4GZTfXEGcP3dSC_PjU4oLE5NS81JL40GAjAyMTQ3MzcwsTR0Nj4lQBAL5cKRM</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS</title><source>esp@cenet</source><creator>ALLOUCHE, Yair ; BILLER, Ofer Haim ; FARCHI, Eitan Daniel ; COHEN, Aviad ; ACKERMAN, Samuel Solomon</creator><creatorcontrib>ALLOUCHE, Yair ; BILLER, Ofer Haim ; FARCHI, Eitan Daniel ; COHEN, Aviad ; ACKERMAN, Samuel Solomon</creatorcontrib><description>An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features using feature grouping. The processor can then detect an anomaly in response to detecting that an associated unbiased outlier score of the sample is higher than a predefined threshold.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2024</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=20240530&DB=EPODOC&CC=US&NR=2024176784A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240530&DB=EPODOC&CC=US&NR=2024176784A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ALLOUCHE, Yair</creatorcontrib><creatorcontrib>BILLER, Ofer Haim</creatorcontrib><creatorcontrib>FARCHI, Eitan Daniel</creatorcontrib><creatorcontrib>COHEN, Aviad</creatorcontrib><creatorcontrib>ACKERMAN, Samuel Solomon</creatorcontrib><title>ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS</title><description>An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features using feature grouping. The processor can then detect an anomaly in response to detecting that an associated unbiased outlier score of the sample is higher than a predefined threshold.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDB1dHEMCPEMc_WJVHB39XMNcgzx9HNX8A8N8fF0DVIIdvYPcg1WCA0GCXp4Bof4uwc5-gbzMLCmJeYUp_JCaW4GZTfXEGcP3dSC_PjU4oLE5NS81JL40GAjAyMTQ3MzcwsTR0Nj4lQBAL5cKRM</recordid><startdate>20240530</startdate><enddate>20240530</enddate><creator>ALLOUCHE, Yair</creator><creator>BILLER, Ofer Haim</creator><creator>FARCHI, Eitan Daniel</creator><creator>COHEN, Aviad</creator><creator>ACKERMAN, Samuel Solomon</creator><scope>EVB</scope></search><sort><creationdate>20240530</creationdate><title>ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS</title><author>ALLOUCHE, Yair ; BILLER, Ofer Haim ; FARCHI, Eitan Daniel ; COHEN, Aviad ; ACKERMAN, Samuel Solomon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2024176784A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>ALLOUCHE, Yair</creatorcontrib><creatorcontrib>BILLER, Ofer Haim</creatorcontrib><creatorcontrib>FARCHI, Eitan Daniel</creatorcontrib><creatorcontrib>COHEN, Aviad</creatorcontrib><creatorcontrib>ACKERMAN, Samuel Solomon</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ALLOUCHE, Yair</au><au>BILLER, Ofer Haim</au><au>FARCHI, Eitan Daniel</au><au>COHEN, Aviad</au><au>ACKERMAN, Samuel Solomon</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS</title><date>2024-05-30</date><risdate>2024</risdate><abstract>An example system includes a processor to receive a stream of records. The processor can generate an unbiased outlier score for each sample in the stream of records via a trained histogram-based outlier score model. The unbiased outlier score is unbiased for samples including dependent features using feature grouping. The processor can then detect an anomaly in response to detecting that an associated unbiased outlier score of the sample is higher than a predefined threshold.</abstract><oa>free_for_read</oa></addata></record>
fulltext	fulltext_linktorsrc
identifier
ispartof
issn
language	eng
recordid	cdi_epo_espacenet_US2024176784A1
source	esp@cenet
subjects	CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
title	ADAPTIVELY GENERATING OUTLIER SCORES USING HISTOGRAMS
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T14%3A29%3A38IST&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=ALLOUCHE,%20Yair&rft.date=2024-05-30&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2024176784A1%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