{"id":"https://openalex.org/W2828944717","doi":"https://doi.org/10.1145/3200947.3201045","title":"An Aggregation Operator for Evaluating Unbounded Positive Evidence","display_name":"An Aggregation Operator for Evaluating Unbounded Positive Evidence","publication_year":2018,"publication_date":"2018-07-06","ids":{"openalex":"https://openalex.org/W2828944717","doi":"https://doi.org/10.1145/3200947.3201045","mag":"2828944717"},"language":"en","primary_location":{"id":"doi:10.1145/3200947.3201045","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3200947.3201045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Hellenic Conference on Artificial Intelligence","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/A5043153150","display_name":"Ilias Kotinas","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Ilias Kotinas","raw_affiliation_strings":["University of Patras"],"affiliations":[{"raw_affiliation_string":"University of Patras","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108443941","display_name":"Nikos Fakotakis","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikos Fakotakis","raw_affiliation_strings":["University of Patras"],"affiliations":[{"raw_affiliation_string":"University of Patras","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5043153150"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08105428,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"92","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10050","display_name":"Multi-Criteria Decision Making","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10050","display_name":"Multi-Criteria Decision Making","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9775999784469604,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.7563480734825134},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.719281017780304},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.7028384804725647},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5587446093559265},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5252470374107361},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.4690176844596863},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.4300713837146759},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.39590713381767273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3735470473766327},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24777689576148987},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24609306454658508},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10445249080657959}],"concepts":[{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.7563480734825134},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.719281017780304},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.7028384804725647},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5587446093559265},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5252470374107361},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.4690176844596863},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.4300713837146759},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.39590713381767273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3735470473766327},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24777689576148987},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24609306454658508},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10445249080657959},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3200947.3201045","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3200947.3201045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Hellenic Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8199999928474426,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W307716697","https://openalex.org/W1479966022","https://openalex.org/W1529718300","https://openalex.org/W1573176374","https://openalex.org/W1584574224","https://openalex.org/W1971788485","https://openalex.org/W1975728475","https://openalex.org/W2047860765","https://openalex.org/W2053237536","https://openalex.org/W2096088275","https://openalex.org/W2117818997","https://openalex.org/W2221996356","https://openalex.org/W2491369943","https://openalex.org/W2510676685","https://openalex.org/W2797148637","https://openalex.org/W2998574808","https://openalex.org/W4232799716","https://openalex.org/W4236588242","https://openalex.org/W4252793191","https://openalex.org/W4301030907","https://openalex.org/W4301347335","https://openalex.org/W6610819985"],"related_works":["https://openalex.org/W2002177687","https://openalex.org/W2058438338","https://openalex.org/W2019471580","https://openalex.org/W2941284322","https://openalex.org/W4224920876","https://openalex.org/W2168299207","https://openalex.org/W4308671316","https://openalex.org/W2920945101","https://openalex.org/W2124475651","https://openalex.org/W2585354854"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,12],"new":[3],"functional":[4],"form":[5],"for":[6,48],"deriving":[7],"an":[8],"aggregate":[9,57],"score":[10,58,97],"from":[11],"possibly":[13],"unbounded":[14],"or":[15,95],"unknown":[16],"number":[17],"of":[18,64,72,105],"inputs":[19],"expressing":[20],"supporting":[21,46,106],"evidence":[22,31,47,66],"along":[23],"with":[24,41,61],"quantified":[25],"confidence":[26],"on":[27],"that":[28,98],"evidence.":[29],"The":[30,86],"indicators":[32],"should":[33,59],"be":[34],"considered":[35],"indepedent":[36],"in":[37,77],"the":[38,49,56,62,70,103],"general":[39],"case,":[40],"each":[42],"one":[43],"contributing":[44],"additional":[45],"case":[50],"under":[51],"analysis.":[52],"In":[53],"these":[54],"settings,":[55],"increase":[60],"amount":[63],"collected":[65],"---":[67,75],"bound":[68],"by":[69,102],"law":[71],"diminishing":[73],"returns":[74],"unlike":[76],"typical":[78],"fusion":[79],"methods":[80],"where":[81],"usually":[82],"averages":[83],"are":[84],"estimated.":[85],"suggested":[87],"operator":[88],"may":[89],"also":[90],"model":[91],"relevance,":[92],"importance,":[93],"association":[94],"any":[96],"is":[99],"mainly":[100],"characterized":[101],"cardinality":[104],"inputs.":[107]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
