{"id":"https://openalex.org/W2548524875","doi":"https://doi.org/10.1145/2980258.2982091","title":"Generating Adaptive Partially Ordered Sequential Rules","display_name":"Generating Adaptive Partially Ordered Sequential Rules","publication_year":2016,"publication_date":"2016-08-25","ids":{"openalex":"https://openalex.org/W2548524875","doi":"https://doi.org/10.1145/2980258.2982091","mag":"2548524875"},"language":"en","primary_location":{"id":"doi:10.1145/2980258.2982091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2980258.2982091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Informatics and Analytics","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/A5015592132","display_name":"Radha Senthilkumar","orcid":"https://orcid.org/0000-0003-2656-4237"},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Radha Senthilkumar","raw_affiliation_strings":["Department of Information Technology, Anna university-MIT campus, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Anna university-MIT campus, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112694719","display_name":"R. Deepika","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Deepika","raw_affiliation_strings":["Department of Information Technology, Anna university-MIT campus, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Anna university-MIT campus, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101451711","display_name":"R. Saranya","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Saranya","raw_affiliation_strings":["Department of Information Technology, Anna university-MIT campus, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Anna university-MIT campus, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075359573","display_name":"Mahesh Govind","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Deepak Govind","raw_affiliation_strings":["Department of Information Technology, Anna university-MIT campus, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Anna university-MIT campus, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33585257"],"apc_list":null,"apc_paid":null,"fwci":0.6904,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.80981555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9828000068664551,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.970300018787384,"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":0.6993235945701599},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6200975775718689},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.49329107999801636},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.4814990758895874},{"id":"https://openalex.org/keywords/semantics-of-business-vocabulary-and-business-rules","display_name":"Semantics of Business Vocabulary and Business Rules","score":0.4609302878379822},{"id":"https://openalex.org/keywords/tree-traversal","display_name":"Tree traversal","score":0.4532932937145233},{"id":"https://openalex.org/keywords/rule-of-inference","display_name":"Rule of inference","score":0.44029465317726135},{"id":"https://openalex.org/keywords/fuzzy-rule","display_name":"Fuzzy rule","score":0.436564564704895},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43429049849510193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4033384919166565},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3489707112312317},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.32097384333610535},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29027265310287476},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.2605443298816681},{"id":"https://openalex.org/keywords/business-rule","display_name":"Business rule","score":0.13437750935554504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6993235945701599},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6200975775718689},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.49329107999801636},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.4814990758895874},{"id":"https://openalex.org/C177688676","wikidata":"https://www.wikidata.org/wiki/Q7449106","display_name":"Semantics of Business Vocabulary and Business Rules","level":5,"score":0.4609302878379822},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.4532932937145233},{"id":"https://openalex.org/C3746660","wikidata":"https://www.wikidata.org/wiki/Q1068763","display_name":"Rule of inference","level":2,"score":0.44029465317726135},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.436564564704895},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43429049849510193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4033384919166565},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3489707112312317},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.32097384333610535},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29027265310287476},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.2605443298816681},{"id":"https://openalex.org/C11066294","wikidata":"https://www.wikidata.org/wiki/Q1518244","display_name":"Business rule","level":4,"score":0.13437750935554504},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.0},{"id":"https://openalex.org/C17409809","wikidata":"https://www.wikidata.org/wiki/Q161764","display_name":"Geochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2980258.2982091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2980258.2982091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Informatics and Analytics","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":16,"referenced_works":["https://openalex.org/W151863654","https://openalex.org/W1577547142","https://openalex.org/W1608194207","https://openalex.org/W1973036367","https://openalex.org/W1990142825","https://openalex.org/W2006251787","https://openalex.org/W2048528401","https://openalex.org/W2084696416","https://openalex.org/W2112971308","https://openalex.org/W2122468393","https://openalex.org/W2123488392","https://openalex.org/W2129836922","https://openalex.org/W2158454296","https://openalex.org/W2166488058","https://openalex.org/W6606194391","https://openalex.org/W6683534485"],"related_works":["https://openalex.org/W170547082","https://openalex.org/W2136735429","https://openalex.org/W2587876411","https://openalex.org/W2358332176","https://openalex.org/W2768881458","https://openalex.org/W4241342595","https://openalex.org/W2980030949","https://openalex.org/W1817111381","https://openalex.org/W2055122450","https://openalex.org/W4306407472"],"abstract_inverted_index":{"Sequential":[0],"rule":[1,132,243,259],"mining":[2,7,155,178],"is":[3,135],"an":[4],"important":[5],"data":[6],"issue":[8],"which":[9,72],"has":[10,61],"numerous":[11],"applications.":[12],"They":[13],"are":[14,82,133,138,152,208],"profoundly":[15],"used":[16,153,209],"in":[17,23,41,50,123,127],"predicting":[18,26],"the":[19,27,32,45,77,101,105,124,128,156,198,221,226,231,238,257,289],"behaviour":[20],"of":[21,38,48,71,100,113,130,170,204,248,263],"learners":[22],"Educational":[24],"data,":[25],"web":[28],"traversal":[29],"patterns,":[30],"finding":[31],"consecutive":[33],"connections":[34],"between":[35,68],"gene":[36],"expressions":[37],"different":[39,246],"patients":[40],"Bio":[42],"Informatics,":[43],"determining":[44],"purchase":[46],"pattern":[47],"customers":[49],"shop":[51],"etc.":[52],"Mining":[53],"for":[54,154,288],"sequential":[55,114,142,179,194],"rules":[56,74,81,87,102,115,171,180,195,228,239],"common":[57,116,181],"to":[58,95,117,167,177,182,197,210,224,255,270,278],"multiple":[59,118,183],"sequences":[60],"some":[62],"drawbacks":[63],"such":[64,120],"as":[65,220],"strict":[66],"ordering":[67],"items,":[69],"because":[70],"several":[73],"may":[75,88],"represent":[76],"same":[78],"situation,":[79],"similar":[80],"rated":[83],"very":[84],"differently":[85],"and,":[86],"be":[89,96],"too":[90],"specific":[91],"and":[92,126,148,161,229,250],"less":[93],"likely":[94],"useful,":[97],"sometimes":[98],"none":[99],"would":[103],"match":[104],"new":[106],"sequence.":[107],"Thus,":[108],"a":[109,272],"more":[110],"broad":[111],"type":[112],"sequences,":[119],"that":[121,200],"items":[122],"forerunner":[125],"resulting":[129],"every":[131],"unordered,":[134],"required.":[136],"These":[137],"called":[139],"partially":[140,192],"ordered":[141,193],"rules.":[143,214,233],"(POSR).":[144],"Rule":[145,159,264,281],"Growth":[146,150,160,163,282,285],"Algorithm":[147,164],"T-Rule":[149,284],"algorithm":[151,266,286],"POSR.":[157],"Both":[158],"TRule":[162],"gives":[165],"rise":[166],"lesser":[168],"number":[169],"with":[172,276],"greater":[173],"prediction":[174],"accuracy":[175],"compared":[176],"sequences.":[184],"The":[185,215,234,261],"proposed":[186],"work":[187],"focuses":[188],"on":[189,241],"making":[190],"these":[191],"adaptive":[196,213],"changes":[199],"occur":[201],"over":[202],"course":[203],"time.":[205],"Two":[206],"approaches":[207],"bring":[211],"out":[212],"first":[216],"approach":[217,236],"uses":[218,251],"rating":[219],"key":[222],"parameter":[223],"eliminate":[225],"weakest":[227],"strengthen":[230],"stronger":[232],"second":[235],"classifies":[237],"based":[240],"their":[242],"scores":[244],"into":[245],"categories":[247],"strength":[249],"fuzzy":[252],"inference":[253],"system":[254],"infer":[256],"incremented":[258],"scores.":[260],"performance":[262],"Rating":[265],"(Incremental":[267],"approach)":[268],"seems":[269],"have":[271],"better":[273],"execution":[274],"time":[275],"respect":[277],"Recomputation":[279],"(i.e":[280],"/":[283],"applied":[287],"entire":[290],"dataset).":[291]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}