{"id":"https://openalex.org/W4390548058","doi":"https://doi.org/10.1145/3632410.3632472","title":"NMNet: Spatial-Temporal Transformer for EEG Signal Analysis in Neuromarketing","display_name":"NMNet: Spatial-Temporal Transformer for EEG Signal Analysis in Neuromarketing","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4390548058","doi":"https://doi.org/10.1145/3632410.3632472"},"language":"en","primary_location":{"id":"doi:10.1145/3632410.3632472","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632410.3632472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th Joint International Conference on Data Science &amp; Management of Data (11th ACM IKDD CODS and 29th COMAD)","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/A5101882843","display_name":"Abhinav Upadhyay","orcid":"https://orcid.org/0000-0001-8201-5959"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abhinav Upadhyay","raw_affiliation_strings":["Accenture Labs, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0001-8201-5959","affiliations":[{"raw_affiliation_string":"Accenture Labs, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016780429","display_name":"Alpana Dubey","orcid":"https://orcid.org/0000-0001-8217-8707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alpana Dubey","raw_affiliation_strings":["Accenture Labs, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0001-8217-8707","affiliations":[{"raw_affiliation_string":"Accenture Labs, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073597647","display_name":"Piyush Goenka","orcid":"https://orcid.org/0009-0006-7474-1655"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piyush Goenka","raw_affiliation_strings":["Accenture Labs, Bangalore, India"],"raw_orcid":"https://orcid.org/0009-0006-7474-1655","affiliations":[{"raw_affiliation_string":"Accenture Labs, Bangalore, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071482252","display_name":"Suma Mani Kuriakose","orcid":"https://orcid.org/0000-0002-5490-9928"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suma Mani Kuriakose","raw_affiliation_strings":["Accenture Labs, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0002-5490-9928","affiliations":[{"raw_affiliation_string":"Accenture Labs, Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101882843"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6509,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6323682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"474","last_page":"478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7742551565170288},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7634062767028809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.585961639881134},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.543059229850769},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5353963971138},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5173611044883728},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4942765235900879},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43994614481925964},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.10872656106948853},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07192569971084595},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06567761301994324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742551565170288},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7634062767028809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.585961639881134},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.543059229850769},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5353963971138},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5173611044883728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4942765235900879},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43994614481925964},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.10872656106948853},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07192569971084595},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06567761301994324},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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:10.1145/3632410.3632472","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632410.3632472","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th Joint International Conference on Data Science &amp; Management of Data (11th ACM IKDD CODS and 29th COMAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2559463885","https://openalex.org/W2595519346","https://openalex.org/W2606700149","https://openalex.org/W3006715270","https://openalex.org/W3101104532","https://openalex.org/W3102455230","https://openalex.org/W4214612132","https://openalex.org/W4293218346"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2047454415","https://openalex.org/W2070040999","https://openalex.org/W2387293848","https://openalex.org/W3121791438","https://openalex.org/W2250140200"],"abstract_inverted_index":{"In":[0,75],"this":[1],"work,":[2],"we":[3,86],"propose":[4],"a":[5,28,49,88,109],"deep":[6],"neural":[7,19],"network,":[8],"NMNet,":[9],"to":[10,31,77,100],"predict":[11],"consumer":[12],"preferences":[13],"for":[14],"E-commerce":[15],"products":[16],"by":[17],"analyzing":[18],"activity":[20],"captured":[21],"through":[22],"EEG":[23,35,54],"signals.":[24],"Our":[25],"approach":[26,47,63],"utilizes":[27],"transformer-based":[29],"model":[30],"extract":[32],"features":[33],"from":[34,57],"signals":[36,55],"in":[37],"both":[38],"the":[39,65,79,94,103],"temporal":[40],"and":[41,68,120],"spatial":[42],"domains.":[43],"We":[44,60],"evaluate":[45,102],"our":[46,62,83,106],"using":[48],"dataset":[50],"consisting":[51],"of":[52,82,91,105,111],"1050":[53],"collected":[56],"25":[58],"participants.":[59],"compare":[61],"against":[64],"existing":[66],"baseline":[67],"consistently":[69],"outperform":[70],"across":[71,108],"all":[72],"evaluation":[73,95],"metrics.":[74],"order":[76],"assess":[78],"generalization":[80],"ability":[81],"proposed":[84],"method,":[85],"employ":[87],"diverse":[89],"set":[90],"stimuli":[92],"during":[93],"phase.":[96],"This":[97],"enables":[98],"us":[99],"thoroughly":[101],"performance":[104],"method":[107],"range":[110],"different":[112],"stimuli,":[113],"providing":[114],"valuable":[115],"insights":[116],"into":[117],"its":[118],"effectiveness":[119],"adaptability.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
