{"id":"https://openalex.org/W4206644595","doi":"https://doi.org/10.1109/bigdata52589.2021.9671444","title":"Human-like Explanation for Text Classification With Limited Attention Supervision","display_name":"Human-like Explanation for Text Classification With Limited Attention Supervision","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206644595","doi":"https://doi.org/10.1109/bigdata52589.2021.9671444"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671444","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5100629138","display_name":"Dongyu Zhang","orcid":"https://orcid.org/0000-0003-2099-5837"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dongyu Zhang","raw_affiliation_strings":["Data Science Program, Worcester Polytechnic Institute, Worcester, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, Worcester Polytechnic Institute, Worcester, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032316925","display_name":"Cansu \u015een","orcid":"https://orcid.org/0000-0003-3355-2736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cansu Sen","raw_affiliation_strings":["CodaMetrix, Boston, USA"],"affiliations":[{"raw_affiliation_string":"CodaMetrix, Boston, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033643173","display_name":"Jidapa Thadajarassiri","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jidapa Thadajarassiri","raw_affiliation_strings":["Data Science Program, Worcester Polytechnic Institute, Worcester, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, Worcester Polytechnic Institute, Worcester, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075881948","display_name":"Thomas Hartvigsen","orcid":"https://orcid.org/0000-0002-5288-2792"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Hartvigsen","raw_affiliation_strings":["Data Science Program, Worcester Polytechnic Institute, Worcester, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, Worcester Polytechnic Institute, Worcester, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002930471","display_name":"Xiangnan Kong","orcid":"https://orcid.org/0000-0002-7403-5869"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangnan Kong","raw_affiliation_strings":["Computer Science Department, Worcester Polytechnic Institute, Worcester, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Worcester Polytechnic Institute, Worcester, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008269094","display_name":"Elke A. Rundensteiner","orcid":"https://orcid.org/0000-0001-5375-9254"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elke Rundensteiner","raw_affiliation_strings":["Computer Science Department, Worcester Polytechnic Institute, Worcester, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Worcester Polytechnic Institute, Worcester, USA","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100629138"],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":0.1257,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.40287904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"957","last_page":"967"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9926000237464905,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9860000014305115,"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/computer-science","display_name":"Computer science","score":0.6109912395477295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39166495203971863},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38549643754959106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6109912395477295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39166495203971863},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38549643754959106}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671444","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2064675550","https://openalex.org/W2079057609","https://openalex.org/W2133280805","https://openalex.org/W2133564696","https://openalex.org/W2250539671","https://openalex.org/W2470673105","https://openalex.org/W2527896214","https://openalex.org/W2571842322","https://openalex.org/W2739918945","https://openalex.org/W2745673637","https://openalex.org/W2759653627","https://openalex.org/W2772853459","https://openalex.org/W2798636921","https://openalex.org/W2859933222","https://openalex.org/W2889436406","https://openalex.org/W2896457183","https://openalex.org/W2898936689","https://openalex.org/W2905110202","https://openalex.org/W2962834107","https://openalex.org/W2962886257","https://openalex.org/W2963082289","https://openalex.org/W2963233086","https://openalex.org/W2963271116","https://openalex.org/W2963630207","https://openalex.org/W2964199361","https://openalex.org/W2965373594","https://openalex.org/W2970155250","https://openalex.org/W3001895040","https://openalex.org/W3034444624","https://openalex.org/W3035503910","https://openalex.org/W3041605817","https://openalex.org/W3095306945","https://openalex.org/W3174254835","https://openalex.org/W4295312788","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6670404919","https://openalex.org/W6679434410","https://openalex.org/W6679915538","https://openalex.org/W6714414533","https://openalex.org/W6726186668","https://openalex.org/W6726804950","https://openalex.org/W6728098186","https://openalex.org/W6732124536","https://openalex.org/W6739901393","https://openalex.org/W6753596224","https://openalex.org/W6755207826","https://openalex.org/W6766673545","https://openalex.org/W6766978945","https://openalex.org/W6784530016"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Human-like":[0,148],"explanation":[1,185],"for":[2,7,86,192],"text":[3,105,181,232],"classification":[4,106,129,182,233],"is":[5,90],"essential":[6],"high-impact":[8],"settings":[9],"such":[10,45,84],"as":[11,220,222],"healthcare":[12],"where":[13],"human":[14,52,56,78,109,166,207],"rationales":[15],"are":[16],"required":[17],"to":[18,29,33,61,67,154,164,205,213,238],"support":[19],"specialists\u2019":[20],"decisions.":[21],"Conventional":[22],"approaches":[23],"learn":[24,156],"explanations":[25],"using":[26],"attention":[27,63,72,79,110,119,157,170,202],"mechanisms":[28,64],"assign":[30],"heavy":[31],"weights":[32,120,158],"words":[34,47,162],"that":[35,159,199],"have":[36],"a":[37,41,68,87,122,133,143,165],"high":[38],"impact":[39],"on":[40,161],"model\u2019s":[42],"prediction.":[43],"However,":[44],"heavily-weighted":[46],"often":[48],"do":[49],"not":[50],"reflect":[51],"intuition.":[53],"To":[54,138],"advance":[55],"rationale,":[57],"recent":[58],"studies":[59],"propose":[60,100],"supervise":[62],"assuming":[65],"access":[66],"huge":[69,88],"set":[70],"of":[71,104,117,180,224],"labels":[73,130,191],"collected":[74],"from":[75,121],"humans,":[76],"called":[77],"maps":[80,203],"(HAMs).":[81],"Unfortunately,":[82],"acquiring":[83],"HAMs":[85],"dataset":[89,123],"very":[91,168],"tedious,":[92],"error-prone,":[93],"and":[94,183],"expensive":[95],"in":[96,124],"practice.":[97],"Thus,":[98],"we":[99,113,141],"the":[101,115,193,225],"novel":[102],"problem":[103],"with":[107,150,167,187,219],"limited":[108,169],"supervision.":[111,171],"Specifically,":[112],"study":[114],"learning":[116,145,176],"human-like":[118],"which":[125],"all":[126],"documents":[127,135,226],"contain":[128],"but":[131],"only":[132,188],"few":[134],"provide":[136],"HAMs.":[137,228],"this":[139],"end,":[140],"design":[142],"deep":[144],"architecture,":[146],"HELAS:":[147],"Explanation":[149],"Limited":[151],"Attention":[152],"Supervision":[153],"adaptively":[155],"focus":[160],"analogous":[163],"HELAS":[172,200],"effectively":[173],"unifies":[174],"joint":[175],"improving":[177],"both":[178],"tasks":[179],"humanlike":[184],"even":[186,218],"insufficient":[189],"supervision":[190],"latter":[194],"task.":[195],"Our":[196],"experiments":[197],"show":[198],"generates":[201],"similar":[204],"real":[206],"annotations":[208],"raising":[209],"similarity":[210],"scores":[211],"up":[212,237],"22%":[214],"over":[215,240],"state-of-the-art":[216,242],"alternatives,":[217],"little":[221],"2%":[223],"having":[227],"It":[229],"concurrently":[230],"improves":[231],"by":[234],"driving":[235],"accuracy":[236],"19%":[239],"four":[241],"methods.":[243]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
