{"id":"https://openalex.org/W2395502593","doi":"https://doi.org/10.5220/0004825601110118","title":"Multi-domain Schema Clustering and Hierarchical Mediated Schema Generation","display_name":"Multi-domain Schema Clustering and Hierarchical Mediated Schema Generation","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2395502593","doi":"https://doi.org/10.5220/0004825601110118","mag":"2395502593"},"language":"en","primary_location":{"id":"doi:10.5220/0004825601110118","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004825601110118","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Enterprise Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0004825601110118","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012046795","display_name":"Qizhen Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qizhen Huang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065997113","display_name":"Chaoliang Zhong","orcid":"https://orcid.org/0000-0003-1697-6932"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaoliang Zhong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100433246","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0003-1017-7179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012046795"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21827066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9979000091552734,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9979000091552734,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9972000122070312,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7168539762496948},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.6325364112854004},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5306424498558044},{"id":"https://openalex.org/keywords/schema-evolution","display_name":"Schema evolution","score":0.4489792585372925},{"id":"https://openalex.org/keywords/database-schema","display_name":"Database schema","score":0.3283703923225403},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3170854449272156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2994750142097473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7168539762496948},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.6325364112854004},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5306424498558044},{"id":"https://openalex.org/C2780660560","wikidata":"https://www.wikidata.org/wiki/Q3951893","display_name":"Schema evolution","level":4,"score":0.4489792585372925},{"id":"https://openalex.org/C30775581","wikidata":"https://www.wikidata.org/wiki/Q632285","display_name":"Database schema","level":3,"score":0.3283703923225403},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3170854449272156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2994750142097473},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004825601110118","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004825601110118","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Enterprise Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0004825601110118","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004825601110118","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Enterprise Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W343945789","https://openalex.org/W1503398984","https://openalex.org/W1968832971","https://openalex.org/W2012656354","https://openalex.org/W2116429057","https://openalex.org/W2153508518","https://openalex.org/W2157631542","https://openalex.org/W2160997301","https://openalex.org/W2171262729","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2585807518","https://openalex.org/W1584107232","https://openalex.org/W2031254074","https://openalex.org/W2148067883","https://openalex.org/W2801431209","https://openalex.org/W2405805678","https://openalex.org/W2117404091","https://openalex.org/W2561775104","https://openalex.org/W3023917735","https://openalex.org/W1545286006"],"abstract_inverted_index":{"A":[0,120],"data":[1,13,20,33],"integration":[2,21],"system":[3],"is":[4],"used":[5],"to":[6,11,35,39,97],"offer":[7],"a":[8,56,71,83,99],"uniform":[9],"interface":[10],"multiple":[12],"sources.":[14],"Previous":[15],"researches":[16],"have":[17],"present":[18],"various":[19],"techniques,":[22],"but":[23,85],"nearly":[24],"all":[25],"of":[26,31,55,82,89,107,114,122,128],"them":[27],"require":[28],"the":[29,40,45,53,80,87,105,112,115,126],"schemas":[30,69,110],"different":[32,49],"sources":[34],"be":[36,52],"integrated":[37],"belong":[38],"same":[41],"domain":[42],"and":[43],"ignore":[44],"fact":[46],"that":[47],"some":[48],"domains":[50,106],"may":[51],"sub-domains":[54,113],"high":[57,117],"level":[58,109,118],"domain.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63],"propose":[64],"an":[65],"approach":[66],"for":[67],"clustering":[68,93],"using":[70],"newly":[72],"defined":[73],"similarity":[74],"measurement":[75],"which":[76],"considers":[77],"not":[78],"only":[79],"attributes":[81],"schema":[84,92,102],"also":[86],"name":[88],"it.":[90],"The":[91],"method":[94],"would":[95],"expose":[96],"users":[98],"hierarchical":[100],"mediated":[101],"forest":[103],"where":[104],"low":[108],"are":[111],"corresponding":[116],"schemas.":[119],"set":[121],"experimental":[123],"results":[124],"demonstrate":[125],"effectiveness":[127],"our":[129],"approach.":[130]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}