{"id":"https://openalex.org/W3204139826","doi":"https://doi.org/10.1109/access.2021.3116467","title":"DKG-PIPD: A Novel Method About Building Deep Knowledge Graph","display_name":"DKG-PIPD: A Novel Method About Building Deep Knowledge Graph","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3204139826","doi":"https://doi.org/10.1109/access.2021.3116467","mag":"3204139826"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3116467","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3116467","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09551950.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09551950.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100323598","display_name":"Yingying Liu","orcid":"https://orcid.org/0000-0002-9565-8416"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]},{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]},{"id":"https://openalex.org/I7726996","display_name":"Henan University of Economic and Law","ror":"https://ror.org/000jtc944","country_code":"CN","type":"education","lineage":["https://openalex.org/I7726996"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingying Liu","raw_affiliation_strings":["Data and Target Engineering College, Information Engineering University, ZhengZhou 450001, China and Information Engineering College, Henan University of Animal Husbandry and Economy, ZhengZhou 450046, China. (e-mail: conslexanve1985@gmx.com)","Information Engineering College, Henan University of Animal Husbandry and Economy, ZhengZhou 450046, China","Data and Target Engineering College, Information Engineering University, ZhengZhou 450001, China"],"raw_orcid":"https://orcid.org/0000-0002-9565-8416","affiliations":[{"raw_affiliation_string":"Data and Target Engineering College, Information Engineering University, ZhengZhou 450001, China and Information Engineering College, Henan University of Animal Husbandry and Economy, ZhengZhou 450046, China. (e-mail: conslexanve1985@gmx.com)","institution_ids":["https://openalex.org/I169689159","https://openalex.org/I7726996"]},{"raw_affiliation_string":"Information Engineering College, Henan University of Animal Husbandry and Economy, ZhengZhou 450046, China","institution_ids":["https://openalex.org/I173899330"]},{"raw_affiliation_string":"Data and Target Engineering College, Information Engineering University, ZhengZhou 450001, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100323598"],"corresponding_institution_ids":["https://openalex.org/I169689159","https://openalex.org/I173899330","https://openalex.org/I7726996"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8189,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78235199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"137295","last_page":"137308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9980999827384949,"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/T11719","display_name":"Data Quality and Management","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8575010299682617},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.7037489414215088},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6958154439926147},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5642103552818298},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5499602556228638},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5495645999908447},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.5469035506248474},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5100684762001038},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4505881369113922},{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.4412650167942047},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43934938311576843},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.41281285881996155},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4109700322151184},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35928183794021606},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.34077954292297363},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15977239608764648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8575010299682617},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.7037489414215088},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6958154439926147},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5642103552818298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5499602556228638},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5495645999908447},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.5469035506248474},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5100684762001038},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4505881369113922},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.4412650167942047},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43934938311576843},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.41281285881996155},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4109700322151184},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35928183794021606},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.34077954292297363},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15977239608764648},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3116467","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3116467","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09551950.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2e486d8266c84891b5620b9e80b6b589","is_oa":true,"landing_page_url":"https://doaj.org/article/2e486d8266c84891b5620b9e80b6b589","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 137295-137308 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3116467","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3116467","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09551950.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3204139826.pdf","grobid_xml":"https://content.openalex.org/works/W3204139826.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W174427690","https://openalex.org/W639708223","https://openalex.org/W1516748551","https://openalex.org/W1566256432","https://openalex.org/W1922773239","https://openalex.org/W1985258458","https://openalex.org/W1996216253","https://openalex.org/W2005424851","https://openalex.org/W2038880450","https://openalex.org/W2070808142","https://openalex.org/W2107598941","https://openalex.org/W2116341502","https://openalex.org/W2127426251","https://openalex.org/W2137079713","https://openalex.org/W2140194939","https://openalex.org/W2187363965","https://openalex.org/W2251135946","https://openalex.org/W2294546627","https://openalex.org/W2499696929","https://openalex.org/W2510830743","https://openalex.org/W2515462165","https://openalex.org/W2530887700","https://openalex.org/W2539469848","https://openalex.org/W2551333235","https://openalex.org/W2556343638","https://openalex.org/W2558286807","https://openalex.org/W2560939934","https://openalex.org/W2605089588","https://openalex.org/W2605634448","https://openalex.org/W2613718673","https://openalex.org/W2794737814","https://openalex.org/W2905462022","https://openalex.org/W2913295164","https://openalex.org/W2920396004","https://openalex.org/W2941274872","https://openalex.org/W2944139570","https://openalex.org/W2962924839","https://openalex.org/W2963041663","https://openalex.org/W2963338481","https://openalex.org/W2963756313","https://openalex.org/W2964161331","https://openalex.org/W2964167098","https://openalex.org/W3003378007","https://openalex.org/W3003546480","https://openalex.org/W3004035003","https://openalex.org/W3012294952","https://openalex.org/W3022086662","https://openalex.org/W3022290554","https://openalex.org/W3022921518","https://openalex.org/W3092243156","https://openalex.org/W3133933710","https://openalex.org/W4285719527","https://openalex.org/W4403853345","https://openalex.org/W6607091552","https://openalex.org/W6631002354","https://openalex.org/W6633947590","https://openalex.org/W6640183791","https://openalex.org/W6724366048","https://openalex.org/W6729959788","https://openalex.org/W6730368328","https://openalex.org/W6745890231","https://openalex.org/W6749856000","https://openalex.org/W6758687673","https://openalex.org/W6784537722","https://openalex.org/W6791216080","https://openalex.org/W6986874642"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2357854711","https://openalex.org/W2369351710","https://openalex.org/W2594363579","https://openalex.org/W4292070284"],"abstract_inverted_index":{"In":[0,99,141],"this":[1,100,178,220],"study,":[2],"a":[3,89,145],"method":[4,92],"about":[5,79],"building":[6,188],"Deep":[7],"Knowledge":[8],"Graph":[9],"for":[10,96,186],"the":[11,22,34,40,46,52,56,64,80,83,102,105,111,128,134,154,167,170,174,182,187,216,226],"Plant":[12],"Insect":[13],"Pest":[14],"and":[15,27,39,60,71,82,104,110,120,151,192,206],"Disease,":[16],"namely":[17],"DKG-PIPD,":[18],"was":[19,30,43,222],"proposed.":[20],"Specifically,":[21],"semi-automatic":[23],"extraction":[24,78,205],"of":[25,36,55,67,136,169,189,219],"semi-structured":[26],"unstructured":[28,86],"knowledge":[29,41,48,72,87,190,207],"carried":[31],"out":[32],"on":[33,153],"basis":[35],"domain":[37,97],"ontology,":[38],"graph":[42],"stored":[44],"in":[45,85,88,177,225],"third-party":[47],"database":[49],"according":[50],"to":[51,62,149],"corpus":[53,90],"characteristic":[54],"plant":[57],"insect":[58],"pest":[59],"disease,":[61],"realize":[63],"visual":[65],"display":[66],"entity":[68,81,103,201,203],"interactive":[69],"relationship":[70,84,106,204],"inference.":[73],"Furthermore,":[74],"DKG-PIPD":[75,143],"performed":[76],"joint":[77],"tagging":[91],"that":[93,198],"is":[94],"suitable":[95],"data.":[98],"way,":[101],"were":[107],"annotated":[108],"synchronically,":[109],"triplet":[112],"can":[113],"be":[114],"obtained":[115],"directly":[116],"through":[117],"label":[118,121],"matching":[119],"mapping,":[122],"which":[123],"not":[124],"only":[125],"effectively":[126],"improved":[127],"annotation":[129],"efficiency,":[130],"but":[131],"also":[132,223],"solved":[133],"problem":[135],"one-versus-many":[137],"overlapping":[138],"relation":[139],"extraction.":[140],"addition,":[142],"used":[144],"novel":[146],"end-to-end":[147],"model":[148],"train":[150],"predict":[152],"crawled":[155],"dataset.":[156],"The":[157],"experimental":[158],"contrast":[159],"results":[160],"with":[161],"other":[162],"classical":[163],"benchmark":[164],"methods":[165],"demonstrated":[166],"effectiveness":[168],"proposed":[171],"method.":[172],"Moreover,":[173],"related":[175],"work":[176],"paper":[179,221],"first":[180],"introduced":[181,224],"general":[183],"architecture":[184],"required":[185],"graph,":[191],"then":[193],"summarized":[194],"its":[195],"key":[196],"points,":[197],"is,":[199],"named":[200],"recognition,":[202],"inference":[208],"using":[209],"deep":[210],"learning":[211],"are":[212],"emphatically":[213],"introduced.":[214],"Finally,":[215],"improvement":[217],"direction":[218],"discussion":[227],"section.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
