{"id":"https://openalex.org/W2946027202","doi":"https://doi.org/10.1145/3318299.3318370","title":"An Interpretable Classification Model Based on Characteristic Element Extraction","display_name":"An Interpretable Classification Model Based on Characteristic Element Extraction","publication_year":2019,"publication_date":"2019-02-22","ids":{"openalex":"https://openalex.org/W2946027202","doi":"https://doi.org/10.1145/3318299.3318370","mag":"2946027202"},"language":"en","primary_location":{"id":"doi:10.1145/3318299.3318370","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","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/A5100778611","display_name":"Mingwei Zhang","orcid":"https://orcid.org/0000-0002-8106-9653"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingwei Zhang","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034119956","display_name":"Xiuxiu He","orcid":"https://orcid.org/0000-0002-8559-9520"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuxiu He","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055136222","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0003-3328-4233"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100778611"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04368112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"344","last_page":"349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9735000133514404,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9735000133514404,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9513999819755554,"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/interpretability","display_name":"Interpretability","score":0.8306114673614502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7714978456497192},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7613446712493896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.709792971611023},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5890318155288696},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.480810284614563},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43781787157058716},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41580620408058167}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8306114673614502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7714978456497192},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7613446712493896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.709792971611023},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5890318155288696},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.480810284614563},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43781787157058716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41580620408058167},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3318299.3318370","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2106525823","https://openalex.org/W2595951082","https://openalex.org/W2744136723","https://openalex.org/W2746793527","https://openalex.org/W2773990282","https://openalex.org/W2780534582","https://openalex.org/W2789553255","https://openalex.org/W2795767639","https://openalex.org/W2809669277","https://openalex.org/W2998768810"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W1986582023","https://openalex.org/W2966829450"],"abstract_inverted_index":{"The":[0,118],"process":[1,13],"of":[2,14,38,44,93,174],"a":[3,97],"classification":[4,18,46,94,106,154,179],"application":[5,19],"is":[6,96,113,121,185],"usually":[7],"dynamic":[8,45],"and":[9,26,71,80,84,126,147,187],"long.":[10],"During":[11],"the":[12,28,35,66,86,91,157,178],"an":[15,51,104],"application,":[16],"better":[17],"effect":[20,92],"can":[21,55,135,148],"be":[22],"acquired":[23],"by":[24,123],"enlarging":[25],"adjusting":[27],"training":[29,87],"dataset":[30],"continuously,":[31],"for":[32,130],"example,":[33],"modifying":[34],"wrong":[36],"labels":[37,133],"original":[39],"instances.":[40],"For":[41],"this":[42,116,183],"kind":[43],"applications,":[47,95],"how":[48],"to":[49,59,69,82,89],"build":[50],"interpretable":[52,105],"classifier":[53,120,165],"which":[54,134],"help":[56,150],"domain":[57,78,151],"experts":[58,152],"understand":[60],"each":[61],"label's":[62],"meanings":[63],"reflected":[64],"from":[65],"dataset,":[67],"then":[68],"compare":[70],"discriminate":[72],"them":[73],"with":[74,171],"their":[75,138],"own":[76],"mastered":[77],"knowledge,":[79],"finally":[81],"adjust":[83],"optimize":[85,153],"set":[88],"enhance":[90],"neglected":[98],"but":[99],"worth":[100],"studying":[101],"issue.":[102],"Therefore,":[103],"model":[107,180],"based":[108],"on":[109],"characteristic":[110,128],"element":[111],"extraction":[112],"proposed":[114,119,181],"in":[115,182,190],"paper.":[117],"constructed":[122],"extracting":[124],"positive":[125],"negative":[127],"elements":[129],"all":[131],"class":[132],"intuitively":[136],"reflect":[137],"instinct":[139],"characteristics.":[140],"Thus,":[141],"it":[142],"has":[143,167],"high":[144],"interpretability":[145],"obviously":[146],"effectively":[149],"effect.":[155],"At":[156],"same":[158],"time,":[159],"experiment":[160],"results":[161],"show":[162],"that":[163],"our":[164],"also":[166],"higher":[168],"accuracy":[169],"compared":[170],"other":[172],"kinds":[173],"classical":[175],"classifiers.":[176],"Consequently,":[177],"paper":[184],"effective":[186],"efficient,":[188],"especially":[189],"practical":[191],"applications.":[192]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}