{"id":"https://openalex.org/W3093246508","doi":"https://doi.org/10.1145/3394171.3413954","title":"Towards More Explainability: Concept Knowledge Mining Network for Event Recognition","display_name":"Towards More Explainability: Concept Knowledge Mining Network for Event Recognition","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093246508","doi":"https://doi.org/10.1145/3394171.3413954","mag":"3093246508"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5044171641","display_name":"Zhaobo Qi","orcid":"https://orcid.org/0000-0001-9196-9818"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaobo Qi","raw_affiliation_strings":["University of Chinese Academy of Sciences &amp; Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences &amp; Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669242","display_name":"Shuhui Wang","orcid":"https://orcid.org/0000-0002-5931-0527"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhui Wang","raw_affiliation_strings":["Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012409526","display_name":"Chi Su","orcid":"https://orcid.org/0000-0002-5117-8867"},"institutions":[{"id":"https://openalex.org/I4210108461","display_name":"Kingsoft (China)","ror":"https://ror.org/01stnfn33","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210108461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Su","raw_affiliation_strings":["Kingsoft Cloud, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kingsoft Cloud, Beijing, China","institution_ids":["https://openalex.org/I4210108461"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088659027","display_name":"Li Su","orcid":"https://orcid.org/0000-0003-4038-753X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Su","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028597017","display_name":"Qingming Huang","orcid":"https://orcid.org/0000-0001-7542-296X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingming Huang","raw_affiliation_strings":["University of Chinese Academy of Sciences &amp; Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences &amp; Inst. of Comput. Tech., Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Cloud BU, Huawei Technologies, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cloud BU, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3857","last_page":"3865"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8236174583435059},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7215046882629395},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6157548427581787},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6061335206031799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5514999032020569},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5352129936218262},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5342110395431519},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5058164596557617},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49228277802467346},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.4835326671600342},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46994808316230774},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4657835066318512},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4489178955554962},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.43936535716056824},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4027141332626343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39116767048835754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8236174583435059},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7215046882629395},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6157548427581787},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6061335206031799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514999032020569},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5352129936218262},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5342110395431519},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5058164596557617},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49228277802467346},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.4835326671600342},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46994808316230774},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4657835066318512},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4489178955554962},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.43936535716056824},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4027141332626343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39116767048835754},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1758470730","https://openalex.org/W1777628566","https://openalex.org/W1927052826","https://openalex.org/W2007731511","https://openalex.org/W2013309773","https://openalex.org/W2016053056","https://openalex.org/W2035607533","https://openalex.org/W2048261712","https://openalex.org/W2065636378","https://openalex.org/W2117539524","https://openalex.org/W2123049467","https://openalex.org/W2136507825","https://openalex.org/W2164587673","https://openalex.org/W2169992457","https://openalex.org/W2194775991","https://openalex.org/W2342662179","https://openalex.org/W2412782625","https://openalex.org/W2472345018","https://openalex.org/W2473032611","https://openalex.org/W2507009361","https://openalex.org/W2520861906","https://openalex.org/W2558122535","https://openalex.org/W2732026016","https://openalex.org/W2777300582","https://openalex.org/W2789221157","https://openalex.org/W2894608918","https://openalex.org/W2896229655","https://openalex.org/W2912684514","https://openalex.org/W2952047972","https://openalex.org/W2963150162","https://openalex.org/W2963315828","https://openalex.org/W2963383024","https://openalex.org/W2963524571","https://openalex.org/W2963526497","https://openalex.org/W2963820951","https://openalex.org/W2964134286","https://openalex.org/W2970671370","https://openalex.org/W2990503944","https://openalex.org/W2995816924","https://openalex.org/W4236965008","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W2357854711","https://openalex.org/W4243448361","https://openalex.org/W2054759342","https://openalex.org/W2051700896","https://openalex.org/W1552255772","https://openalex.org/W2111524952","https://openalex.org/W4234690372","https://openalex.org/W4239551281","https://openalex.org/W2103484298","https://openalex.org/W1996233288"],"abstract_inverted_index":{"Event":[0],"recognition":[1],"of":[2,49,99,127,150,173],"untrimmed":[3],"video":[4],"is":[5,97,180],"a":[6,87,118],"challenging":[7],"task":[8],"due":[9],"to":[10,116],"the":[11,45,63,82,124,145,168],"big":[12],"gap":[13],"between":[14,66,147],"low":[15],"level":[16],"visual":[17],"features":[18],"and":[19,73,107,139,162,170],"event":[20,35,94,177],"semantics.":[21],"Beyond":[22],"feature":[23],"learning":[24],"via":[25],"deep":[26],"neural":[27],"networks,":[28],"some":[29],"recent":[30],"works":[31],"focus":[32],"on":[33,58,160,176],"analyzing":[34],"videos":[36],"using":[37],"concept-based":[38],"representation.":[39],"However,":[40],"these":[41],"methods":[42],"simply":[43],"aggregate":[44],"concept":[46,60,68,88,102,110,120,129],"representation":[47,121],"vectors":[48],"frames":[50],"or":[51],"segments,":[52],"which":[53],"inevitably":[54],"introduces":[55],"information":[56],"loss":[57],"video-level":[59],"knowledge.":[61],"Moreover,":[62],"diversified":[64],"relation":[65],"different":[67,131,148],"domains":[69],"(e.g.,":[70],"scene,":[71],"object":[72],"action)":[74],"has":[75],"not":[76],"been":[77],"fully":[78],"explored.":[79],"To":[80],"address":[81],"above":[83],"issues,":[84],"we":[85],"propose":[86],"knowledge":[89,103,111],"mining":[90,104,112,123],"network":[91],"(CKMN)":[92],"for":[93],"recognition.":[95],"CKMN":[96],"composed":[98],"an":[100,108],"intra-domain":[101],"subnetwork":[105],"(IaCKM)":[106],"inter-domain":[109],"subnetwork~(IrCKM).":[113],"IaCKM":[114],"aims":[115],"obtain":[117],"complete":[119],"by":[122],"existing":[125],"pattern":[126],"each":[128],"at":[130,182],"time":[132],"granularities":[133],"with":[134,152],"dilated":[135],"temporal":[136,140],"pyramid":[137],"convolution":[138],"self-attention,":[141],"while":[142],"IrCKM":[143],"explores":[144],"interaction":[146],"types":[149],"concepts":[151],"co-attention":[153],"style":[154],"learning.":[155],"We":[156],"evaluate":[157],"our":[158,174],"method":[159],"FCVID":[161],"ActivityNet":[163],"datasets.":[164],"Experimental":[165],"results":[166],"show":[167],"effectiveness":[169],"better":[171],"interpretability":[172],"model":[175],"analytics.":[178],"Code":[179],"available":[181],"https://github.com/qzhb/CKMN.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
