{"id":"https://openalex.org/W2004368128","doi":"https://doi.org/10.1109/coginf.2010.5599780","title":"Hierarchical Multi-label Associative Classification (HMAC) using negative rules","display_name":"Hierarchical Multi-label Associative Classification (HMAC) using negative rules","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2004368128","doi":"https://doi.org/10.1109/coginf.2010.5599780","mag":"2004368128"},"language":"en","primary_location":{"id":"doi:10.1109/coginf.2010.5599780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","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/A5006312923","display_name":"Sawinee Sangsuriyun","orcid":"https://orcid.org/0000-0003-4897-2426"},"institutions":[{"id":"https://openalex.org/I198105771","display_name":"Kasetsart University","ror":"https://ror.org/05gzceg21","country_code":"TH","type":"education","lineage":["https://openalex.org/I198105771"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sawinee Sangsuriyun","raw_affiliation_strings":["Computer Engineering Department, Faculty of Engineering, Kasetsart University, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Faculty of Engineering, Kasetsart University, Thailand","institution_ids":["https://openalex.org/I198105771"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043447596","display_name":"Sanparith Marukatat","orcid":"https://orcid.org/0000-0002-8508-8544"},"institutions":[{"id":"https://openalex.org/I14316845","display_name":"National Electronics and Computer Technology Center","ror":"https://ror.org/04z82ry91","country_code":"TH","type":"government","lineage":["https://openalex.org/I1332092204","https://openalex.org/I14316845"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sanparith Marukatat","raw_affiliation_strings":["Image Laboratory, NECTEC, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Laboratory, NECTEC, Thailand","institution_ids":["https://openalex.org/I14316845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012602048","display_name":"Kitsana Waiyamai","orcid":null},"institutions":[{"id":"https://openalex.org/I198105771","display_name":"Kasetsart University","ror":"https://ror.org/05gzceg21","country_code":"TH","type":"education","lineage":["https://openalex.org/I198105771"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Kitsana Waiyamai","raw_affiliation_strings":["Computer Engineering Department, Faculty of Engineering, Kasetsart University, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Faculty of Engineering, Kasetsart University, Thailand","institution_ids":["https://openalex.org/I198105771"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0899,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7669467,"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":"919","last_page":"924"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9991999864578247,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9991999864578247,"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":0.9897000193595886,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9889000058174133,"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/jaccard-index","display_name":"Jaccard index","score":0.882581353187561},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6940572261810303},{"id":"https://openalex.org/keywords/associative-property","display_name":"Associative property","score":0.6361637115478516},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5954574346542358},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5614771246910095},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5121140480041504},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46236398816108704},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4492649734020233},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4235341548919678},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20185422897338867}],"concepts":[{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.882581353187561},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940572261810303},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.6361637115478516},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5954574346542358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5614771246910095},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5121140480041504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46236398816108704},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4492649734020233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4235341548919678},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20185422897338867},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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:10.1109/coginf.2010.5599780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W60969841","https://openalex.org/W204528376","https://openalex.org/W1488440450","https://openalex.org/W1496655772","https://openalex.org/W1578151950","https://openalex.org/W1623342295","https://openalex.org/W1907020532","https://openalex.org/W1966666559","https://openalex.org/W1987869189","https://openalex.org/W2091961126","https://openalex.org/W2092258934","https://openalex.org/W2100567627","https://openalex.org/W2100935296","https://openalex.org/W2103237310","https://openalex.org/W2115866740","https://openalex.org/W2117805756","https://openalex.org/W2118921819","https://openalex.org/W2123489126","https://openalex.org/W2123504579","https://openalex.org/W2135103397","https://openalex.org/W2138091718","https://openalex.org/W2146241755","https://openalex.org/W2154642793","https://openalex.org/W2162738964","https://openalex.org/W2167681385","https://openalex.org/W2170519978","https://openalex.org/W2466512847","https://openalex.org/W2950225692","https://openalex.org/W2953332543","https://openalex.org/W4285719527","https://openalex.org/W6602551626","https://openalex.org/W6675339850","https://openalex.org/W6677712588","https://openalex.org/W6678207380","https://openalex.org/W6682837551","https://openalex.org/W6684495928","https://openalex.org/W7055702063"],"related_works":["https://openalex.org/W4254879869","https://openalex.org/W3022576529","https://openalex.org/W2628526247","https://openalex.org/W2596401011","https://openalex.org/W2913569734","https://openalex.org/W3127229356","https://openalex.org/W2000801317","https://openalex.org/W2294604808","https://openalex.org/W2749089722","https://openalex.org/W2148338580"],"abstract_inverted_index":{"Hierarchical":[0,15,42],"Classification":[1],"is":[2,19,121],"a":[3,12,94],"very":[4],"important":[5],"classification":[6,88],"task":[7],"for":[8,78,85],"arranging":[9],"data":[10,18],"in":[11,61],"hierarchical":[13,86,108,139],"structure.":[14],"arrangement":[16],"of":[17,21,29,70,111,138],"one":[20],"the":[22,37,71],"best":[23],"methods":[24],"to":[25,40,53,57,63,106],"achieve":[26],"better":[27],"understanding":[28],"complex":[30],"data.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,92],"propose":[36,93],"HMAC":[38,132],"method":[39,47,77,84],"perform":[41],"Multi-label":[43],"Associative":[44],"Classification.":[45],"This":[46],"uses":[48],"multiple":[49],"and":[50,56,67,81,103,113,123,135,146],"negative":[51,79],"rules":[52,80],"predict":[54],"class-set":[55],"filter":[58],"exceptional":[59],"cases":[60],"order":[62],"improve":[64],"both":[65],"accuracy":[66,134],"explanatory":[68,136],"ability":[69,137],"resulting":[72],"classifier.":[73],"Redundant":[74],"rule":[75,82,95,125,144],"pruning":[76,147],"ranking":[83,145],"associative":[87],"are":[89],"developed.":[90],"Moreover,":[91],"evaluation":[96,126],"measure,":[97],"Sim,":[98],"that":[99,119,131],"tread-off":[100],"between":[101],"F-measure":[102],"Jaccard's":[104],"coefficient":[105],"encode":[107],"structure":[109],"meaning":[110],"actual":[112],"predicted":[114],"node":[115],"collections.":[116],"We":[117],"show":[118,130],"Sim":[120],"robust":[122],"simple":[124],"measure.":[127],"Experimental":[128],"results":[129],"improves":[133],"classifiers":[140],"compared":[141],"with":[142],"various":[143],"techniques.":[148]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
