{"id":"https://openalex.org/W2106563527","doi":"https://doi.org/10.1109/wkdd.2009.143","title":"Multi Relational Rules Mining in Data Warehouse","display_name":"Multi Relational Rules Mining in Data Warehouse","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W2106563527","doi":"https://doi.org/10.1109/wkdd.2009.143","mag":"2106563527"},"language":"en","primary_location":{"id":"doi:10.1109/wkdd.2009.143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wkdd.2009.143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","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/A5052676996","display_name":"Youdong Zhang","orcid":"https://orcid.org/0009-0000-8351-9091"},"institutions":[{"id":"https://openalex.org/I4210153869","display_name":"Huaiyin Institute of Technology","ror":"https://ror.org/0555ezg60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153869"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Youdong Zhang","raw_affiliation_strings":["Dept. of Comput. Eng., Huaiyin Inst. of Technol., Huaian"],"affiliations":[{"raw_affiliation_string":"Dept. of Comput. Eng., Huaiyin Inst. of Technol., Huaian","institution_ids":["https://openalex.org/I4210153869"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5052676996"],"corresponding_institution_ids":["https://openalex.org/I4210153869"],"apc_list":null,"apc_paid":null,"fwci":0.7403,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82958516,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"944","last_page":"947"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9886999726295471,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9714000225067139,"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/data-warehouse","display_name":"Data warehouse","score":0.755967378616333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.753577709197998},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.7073067426681519},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7005792260169983},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.6707121133804321},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.6125466823577881},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.41141289472579956},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.4033508896827698},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3588169813156128}],"concepts":[{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.755967378616333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753577709197998},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.7073067426681519},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7005792260169983},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.6707121133804321},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.6125466823577881},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.41141289472579956},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.4033508896827698},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3588169813156128}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wkdd.2009.143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wkdd.2009.143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","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":22,"referenced_works":["https://openalex.org/W1490466294","https://openalex.org/W1506152736","https://openalex.org/W1513527572","https://openalex.org/W1515653062","https://openalex.org/W1538904412","https://openalex.org/W1550343688","https://openalex.org/W1636712341","https://openalex.org/W2021321535","https://openalex.org/W2033072307","https://openalex.org/W2091254164","https://openalex.org/W2109597229","https://openalex.org/W2109603199","https://openalex.org/W2113243831","https://openalex.org/W2126256482","https://openalex.org/W2133403996","https://openalex.org/W2158292827","https://openalex.org/W2611164949","https://openalex.org/W2769909413","https://openalex.org/W4285719527","https://openalex.org/W6630879526","https://openalex.org/W6636676441","https://openalex.org/W6719316343"],"related_works":["https://openalex.org/W2751920613","https://openalex.org/W2415164632","https://openalex.org/W2238349241","https://openalex.org/W2355668701","https://openalex.org/W2370453500","https://openalex.org/W2099525665","https://openalex.org/W1561334777","https://openalex.org/W3012205960","https://openalex.org/W2079402849","https://openalex.org/W2522980826"],"abstract_inverted_index":{"Multi":[0],"relational":[1,33,104],"rules":[2,58,79],"mining":[3,10,71],"is":[4,19,24,30,62],"a":[5,32,36,53,97],"new":[6,54],"area":[7],"of":[8,15,50],"data":[9,60,65,107],"research.":[11],"There":[12],"three":[13],"kinds":[14],"algorithm":[16,72,76],"currently.":[17],"One":[18],"ILP":[20],"approach,":[21,27],"the":[22,48,78,88,103],"second":[23],"AVL":[25],"upgrading":[26],"and\u00a0\u00a0the":[28],"last":[29],"mould":[31],"database":[34],"into":[35],"single":[37,43,89],"table":[38,44,82],"to":[39,47,56,83,101],"mine":[40,57],"with":[41],"traditionally":[42],"technology.":[45],"Due":[46],"drawback":[49],"these":[51],"methods,":[52],"ideal":[55],"in":[59,106],"warehouse":[61],"proposed.":[63],"The":[64,75,92],"schema":[66],"constructing,":[67],"primitive":[68],"language":[69],"and":[70],"are":[73],"analysis.":[74],"concerns":[77],"from":[80],"one":[81],"another":[84],"only,":[85],"but":[86],"considers":[87],"table\u2019s":[90],"rules.":[91],"experiments":[93],"show":[94],"it":[95],"has":[96],"good":[98],"accuracy":[99],"due":[100],"utilize":[102],"information":[105],"warehouse.":[108]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
