{"id":"https://openalex.org/W2783744756","doi":"https://doi.org/10.1109/bigdata.2017.8258091","title":"A cognitive assistant for risk identification and modeling","display_name":"A cognitive assistant for risk identification and modeling","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783744756","doi":"https://doi.org/10.1109/bigdata.2017.8258091","mag":"2783744756"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052501780","display_name":"Dharmashankar Subramanian","orcid":"https://orcid.org/0000-0002-1990-7740"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dharmashankar Subramanian","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021181010","display_name":"Debarun Bhattachrajya","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debarun Bhattachrajya","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY, US"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY, US","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022307512","display_name":"Rub\u00e9n Rodr\u00edguez Torrado","orcid":null},"institutions":[{"id":"https://openalex.org/I66855515","display_name":"Repsol (Spain)","ror":"https://ror.org/028bzjj61","country_code":"ES","type":"company","lineage":["https://openalex.org/I66855515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ruben R. Torrado","raw_affiliation_strings":["Repsol S.A., Madrid, Spain"],"affiliations":[{"raw_affiliation_string":"Repsol S.A., Madrid, Spain","institution_ids":["https://openalex.org/I66855515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113695961","display_name":"Jeff Kephart","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeff Kephart","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058823844","display_name":"Vijil Chenthamarakshan","orcid":"https://orcid.org/0000-0001-7830-5777"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vijil Chenthamarakshan","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044827158","display_name":"Jes\u00fas R\u00edos","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jesus Rios","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5052501780"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.72398723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"34","issue":null,"first_page":"1570","last_page":"1579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7948576211929321},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.531046450138092},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.498260498046875},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.46054548025131226},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4552809000015259},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.43532004952430725},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3728273808956146},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.11896371841430664},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1120789647102356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7948576211929321},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.531046450138092},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.498260498046875},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.46054548025131226},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4552809000015259},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.43532004952430725},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3728273808956146},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.11896371841430664},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1120789647102356},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8258091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W152377028","https://openalex.org/W1015225754","https://openalex.org/W1647976003","https://openalex.org/W1975700576","https://openalex.org/W1986386500","https://openalex.org/W1995695215","https://openalex.org/W2031999958","https://openalex.org/W2058150410","https://openalex.org/W2068189605","https://openalex.org/W2076995980","https://openalex.org/W2078571616","https://openalex.org/W2099938389","https://openalex.org/W2101114896","https://openalex.org/W2118020653","https://openalex.org/W2135631407","https://openalex.org/W2141373701","https://openalex.org/W2147627663","https://openalex.org/W2157253272","https://openalex.org/W2250539671","https://openalex.org/W2398199884","https://openalex.org/W2504136459","https://openalex.org/W2528321558","https://openalex.org/W2798829742","https://openalex.org/W2913758949","https://openalex.org/W4298191365","https://openalex.org/W6682969156","https://openalex.org/W6712373679","https://openalex.org/W6758622208"],"related_works":["https://openalex.org/W1923764247","https://openalex.org/W2114208415","https://openalex.org/W2369233745","https://openalex.org/W2125534874","https://openalex.org/W2611614597","https://openalex.org/W2313821829","https://openalex.org/W2619501344","https://openalex.org/W4386500624","https://openalex.org/W2899303483","https://openalex.org/W4240788009"],"abstract_inverted_index":{"Economic":[0],"systems":[1],"are":[2,148,159],"rife":[3],"with":[4,63,80,90,118,135,216],"heterogeneous":[5],"risk":[6,18,28,44,48,73,83,125,137,190,205,214],"events":[7,191],"that":[8,59,147,158,186],"have":[9],"the":[10,64,70,113,136,163,176,209,217],"potential":[11],"to":[12,25,161,211],"cause":[13],"disruption.":[14],"The":[15,35],"diversity":[16],"of":[17,66,72,94,104,184,219],"types":[19],"makes":[20],"it":[21],"challenging":[22],"for":[23,30,127],"companies":[24],"conduct":[26],"comprehensive":[27,82],"analysis":[29,74],"any":[31],"chosen":[32],"business":[33],"opportunity.":[34],"current":[36],"practice":[37],"is":[38,78,116],"laborious":[39],"and":[40,46,85,109,121,130,174],"expensive,":[41],"involving":[42],"internal":[43],"analysts":[45],"external":[47],"advisory":[49],"services.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,179],"present":[55],"a":[56,81,102,124,140,151,171,181,197,204,213,220],"cognitive":[57],"system":[58,77,133,210],"augments":[60],"human":[61],"abilities,":[62],"objective":[65],"drastic":[67],"improvements":[68],"in":[69,123],"productivity":[71],"efforts.":[75],"Our":[76,132],"provided":[79],"taxonomy":[84],"its":[86],"textual":[87,95,105],"description":[88],"along":[89],"an":[91],"extensive":[92],"corpus":[93,115],"data":[96,114],"such":[97],"as":[98,193],"news":[99],"articles.":[100],"Using":[101],"series":[103],"analysis,":[106],"knowledge":[107],"extraction":[108],"machine":[110],"learning":[111],"techniques,":[112],"annotated":[117],"risk-related":[119,165],"information":[120],"indexed":[122],"store":[126],"flexible":[128],"query":[129,141,208],"retrieval.":[131],"interfaces":[134],"analyst":[138,145,206],"using":[139],"orchestrator":[142],"which":[143],"translates":[144],"queries":[146,157],"posed":[149],"at":[150],"high":[152],"level":[153,156],"into":[154],"lower":[155],"expanded":[160],"exploit":[162],"system's":[164],"knowledge.":[166],"It":[167],"also":[168],"enables":[169],"formulating":[170],"graphical":[172],"model":[173,215],"assessing":[175],"required":[177],"probabilities;":[178],"introduce":[180],"particular":[182],"family":[183],"models":[185],"can":[187,207],"succinctly":[188],"represent":[189],"modeled":[192],"stochastic":[194],"processes":[195],"over":[196],"long":[198],"time":[199],"horizon.":[200],"We":[201],"illustrate":[202],"how":[203],"build":[212],"help":[218],"case":[221],"study.":[222]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}