{"id":"https://openalex.org/W2097202152","doi":"https://doi.org/10.1109/fskd.2011.6019901","title":"A post-processing approach to Chinese address recognition","display_name":"A post-processing approach to Chinese address recognition","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2097202152","doi":"https://doi.org/10.1109/fskd.2011.6019901","mag":"2097202152"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2011.6019901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2011.6019901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5068562966","display_name":"Xinyu Yao","orcid":"https://orcid.org/0000-0003-4554-5592"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyu Yao","raw_affiliation_strings":["Department of Computer Science & Technology, East China Normal University, Shanghai, China","Department of Computer Science and Technology,East China Normal University,Shanghai 200241,china"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Department of Computer Science and Technology,East China Normal University,Shanghai 200241,china","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031868292","display_name":"Yue Lu","orcid":"https://orcid.org/0000-0003-4062-6553"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Lu","raw_affiliation_strings":["Department of Computer Science & Technology, East China Normal University, Shanghai, China","Department of Computer Science and Technology,East China Normal University,Shanghai 200241,china"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Department of Computer Science and Technology,East China Normal University,Shanghai 200241,china","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068562966"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.16234879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"1906","last_page":"1910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9973999857902527,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9973999857902527,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9961000084877014,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.8245016932487488},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5497550964355469},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.46883028745651245},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.45387521386146545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45380499958992004},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4505149722099304},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4500857889652252},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43443483114242554},{"id":"https://openalex.org/keywords/pinyin","display_name":"Pinyin","score":0.42705437541007996},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4256490468978882},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3981500267982483},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.09343090653419495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245016932487488},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5497550964355469},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.46883028745651245},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.45387521386146545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45380499958992004},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4505149722099304},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4500857889652252},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43443483114242554},{"id":"https://openalex.org/C2781095461","wikidata":"https://www.wikidata.org/wiki/Q42222","display_name":"Pinyin","level":3,"score":0.42705437541007996},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4256490468978882},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3981500267982483},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.09343090653419495},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2011.6019901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2011.6019901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7099999785423279,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2001496424","https://openalex.org/W2008946920","https://openalex.org/W2123496204","https://openalex.org/W2152574989","https://openalex.org/W2362157790","https://openalex.org/W2379780306","https://openalex.org/W6678560295","https://openalex.org/W7012093042"],"related_works":["https://openalex.org/W2169386488","https://openalex.org/W2398174936","https://openalex.org/W1991876791","https://openalex.org/W2274846632","https://openalex.org/W64654948","https://openalex.org/W421533916","https://openalex.org/W2098748517","https://openalex.org/W1566315437","https://openalex.org/W2377224690","https://openalex.org/W2594897229"],"abstract_inverted_index":{"In":[0,55],"recent":[1],"years,":[2],"it":[3],"has":[4],"become":[5],"a":[6,60,102],"focus":[7],"to":[8,16,38,97,122,142],"make":[9],"use":[10,42],"of":[11,20,43],"the":[12,18,27,33,41,44,52,79,91,116,125,136,145],"address":[13,29,45,64,70],"recognition":[14,53],"technology":[15],"improve":[17,51],"performance":[19],"mail":[21],"sorting":[22],"machines.":[23],"The":[24,63],"research":[25],"in":[26,47,106],"postal":[28],"recognition,":[30],"which":[31,95],"extends":[32],"context":[34],"relation":[35],"from":[36,120,140],"words":[37],"sentences":[39],"with":[40,82],"information":[46],"post-processing,":[48,111],"can":[49],"effectively":[50],"performance.":[54],"this":[56],"paper,":[57],"we":[58],"propose":[59],"divide-and-rule":[61],"method.":[62],"is":[65,85,99,108],"divided":[66],"into":[67],"high":[68,76,113],"level":[69,73,77,89,114,134],"and":[71,131],"low":[72,88,133],"address.":[74],"For":[75,87],"address,":[78,90,115,135],"similarity":[80,104],"method":[81,105],"HLA":[83],"database":[84],"presented.":[86],"Syllable-based":[92],"language":[93],"model":[94],"applies":[96],"Pinyin":[98],"discussed.":[100],"Then":[101],"new":[103],"multi-mode":[107],"introduced.":[109],"After":[110],"for":[112,132],"hit":[117,137],"rate":[118,127,138,147],"rises":[119],"87.63%":[121],"95.12%":[123],"while":[124,144],"accuracy":[126,146],"declines":[128],"by":[129,149],"2.67%,":[130],"increases":[139],"58.16%":[141],"91.81%":[143],"decreases":[148],"9.40%.":[150]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
