{"id":"https://openalex.org/W2326489462","doi":"https://doi.org/10.1080/10798587.2016.1158498","title":"An Integration Model of Semantic Annotation Based on Synergetic Neural Network","display_name":"An Integration Model of Semantic Annotation Based on Synergetic Neural Network","publication_year":2016,"publication_date":"2016-03-21","ids":{"openalex":"https://openalex.org/W2326489462","doi":"https://doi.org/10.1080/10798587.2016.1158498","mag":"2326489462"},"language":"en","primary_location":{"id":"doi:10.1080/10798587.2016.1158498","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2016.1158498","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-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/A5081963904","display_name":"Zhehuang Huang","orcid":"https://orcid.org/0000-0002-2912-5240"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhehuang Huang","raw_affiliation_strings":["School of Mathematics Sciences, Huaqiao University, Quanzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics Sciences, Huaqiao University, Quanzhou, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100689058","display_name":"Yidong Chen","orcid":"https://orcid.org/0000-0002-0243-7228"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidong Chen","raw_affiliation_strings":["[Cognitive Science Department, Xiamen University, Xiamen, China]"],"affiliations":[{"raw_affiliation_string":"[Cognitive Science Department, Xiamen University, Xiamen, China]","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081963904"],"corresponding_institution_ids":["https://openalex.org/I119045251"],"apc_list":null,"apc_paid":null,"fwci":0.857,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82959405,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"22","issue":"3","first_page":"525","last_page":"532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9922000169754028,"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":0.9432228803634644},{"id":"https://openalex.org/keywords/semantic-annotation","display_name":"Semantic annotation","score":0.6542026996612549},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5621288418769836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5413861274719238},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5317486524581909},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4117283821105957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9432228803634644},{"id":"https://openalex.org/C2985727698","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Semantic annotation","level":3,"score":0.6542026996612549},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5621288418769836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5413861274719238},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5317486524581909},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4117283821105957}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10798587.2016.1158498","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2016.1158498","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W11155487","https://openalex.org/W111475876","https://openalex.org/W1012949241","https://openalex.org/W1497042422","https://openalex.org/W1526679311","https://openalex.org/W1593271688","https://openalex.org/W1598286016","https://openalex.org/W1966250206","https://openalex.org/W1970563495","https://openalex.org/W1970849810","https://openalex.org/W2000606471","https://openalex.org/W2005309629","https://openalex.org/W2015707701","https://openalex.org/W2021399367","https://openalex.org/W2040776591","https://openalex.org/W2040991551","https://openalex.org/W2061871963","https://openalex.org/W2088911157","https://openalex.org/W2091129519","https://openalex.org/W2101454539","https://openalex.org/W2101837219","https://openalex.org/W2104948038","https://openalex.org/W2108402998","https://openalex.org/W2115557995","https://openalex.org/W2134478050","https://openalex.org/W2136925175","https://openalex.org/W2138043057","https://openalex.org/W2142222368","https://openalex.org/W2142340904","https://openalex.org/W2148125485","https://openalex.org/W2152195021","https://openalex.org/W2153252986","https://openalex.org/W2166952856","https://openalex.org/W2373775216","https://openalex.org/W2618735189","https://openalex.org/W2733628661","https://openalex.org/W2892737606","https://openalex.org/W4240301415","https://openalex.org/W4242752819","https://openalex.org/W4285719527","https://openalex.org/W4383988640"],"related_works":["https://openalex.org/W3192589309","https://openalex.org/W2369337446","https://openalex.org/W4385569300","https://openalex.org/W2889470921","https://openalex.org/W2574165153","https://openalex.org/W2251095918","https://openalex.org/W2206855020","https://openalex.org/W2105339902","https://openalex.org/W2972508764","https://openalex.org/W1978635732"],"abstract_inverted_index":{"AbstractCorrect":[0],"and":[1,40,94,119],"automatical":[2],"semantic":[3,23,31,36,71,97,108,121,137],"analysis":[4,32,72,98,138],"has":[5],"always":[6],"been":[7],"one":[8],"of":[9,30,107],"major":[10],"goals":[11],"in":[12,21,82,131],"natural":[13],"language":[14],"understanding.":[15],"However,":[16,55],"due":[17],"to":[18,65],"the":[19,27,67,104],"difficulties":[20],"deep":[22],"analysis,":[24],"at":[25],"present,":[26],"mainstream":[28],"studies":[29],"are":[33,49,127],"focused":[34],"on":[35,75],"role":[37],"labeling":[38],"(SRL)":[39],"word":[41,145],"sense":[42,146],"disambiguation":[43],"(WSD).":[44],"Nowadays,":[45],"these":[46],"two":[47],"issues":[48],"mostly":[50],"considered":[51],"as":[52,103],"separate":[53],"tasks.":[54],"this":[56,83,132],"approach":[57],"ignores":[58],"possible":[59],"dependencies":[60],"between":[61,92],"them.":[62],"In":[63],"order":[64,109,113],"address":[66],"issue,":[68],"an":[69,135],"integrative":[70,136],"model":[73,139],"based":[74],"synergetic":[76],"neural":[77],"network":[78],"(SNN)":[79],"is":[80,140],"proposed":[81,141],"paper,":[84],"which":[85],"can":[86,100],"easily":[87],"express":[88],"useful":[89],"logic":[90],"constraints":[91],"SRL":[93],"WSD.":[95],"The":[96,111],"process":[99,106],"be":[101,124],"viewed":[102],"competition":[105,118],"parameters.":[110],"strongest":[112],"parameter":[114],"will":[115,123],"win":[116],"by":[117],"desired":[120],"patterns":[122],"recognized.":[125],"There":[126],"three":[128],"main":[129],"innovations":[130],"paper.":[133],"First,":[134],"that":[142],"jointly":[143],"models":[144],"disambiguationand...":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}