{"id":"https://openalex.org/W3023947208","doi":"https://doi.org/10.1145/3384544.3384582","title":"BGSGA","display_name":"BGSGA","publication_year":2020,"publication_date":"2020-02-18","ids":{"openalex":"https://openalex.org/W3023947208","doi":"https://doi.org/10.1145/3384544.3384582","mag":"3023947208"},"language":"en","primary_location":{"id":"doi:10.1145/3384544.3384582","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3384544.3384582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 9th International Conference on Software and Computer Applications","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/A5059166506","display_name":"Peng Chengcheng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengcheng Peng","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101432128","display_name":"Bin Wu","orcid":"https://orcid.org/0000-0002-7112-126X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wu","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102847749","display_name":"Zekun Li","orcid":"https://orcid.org/0000-0003-2798-4145"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zekun Li","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059166506"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04700735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9965000152587891,"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":0.8777148723602295},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7318664789199829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6921987533569336},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6264299750328064},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5924695134162903},{"id":"https://openalex.org/keywords/word-order","display_name":"Word order","score":0.5361018180847168},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5002703666687012},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.48133477568626404},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.46705830097198486},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.4652344584465027},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.43632790446281433},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4362068772315979},{"id":"https://openalex.org/keywords/syntactic-structure","display_name":"Syntactic structure","score":0.43598148226737976},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.4323922395706177},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.429439902305603},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.41891419887542725},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3406578302383423},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.28657758235931396},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.2142433226108551},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10766631364822388},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.084748774766922}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8777148723602295},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7318664789199829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6921987533569336},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6264299750328064},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5924695134162903},{"id":"https://openalex.org/C70777604","wikidata":"https://www.wikidata.org/wiki/Q257885","display_name":"Word order","level":2,"score":0.5361018180847168},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5002703666687012},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.48133477568626404},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.46705830097198486},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.4652344584465027},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.43632790446281433},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4362068772315979},{"id":"https://openalex.org/C2986991398","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntactic structure","level":3,"score":0.43598148226737976},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.4323922395706177},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.429439902305603},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.41891419887542725},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3406578302383423},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.28657758235931396},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2142433226108551},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10766631364822388},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.084748774766922},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3384544.3384582","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3384544.3384582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 9th International Conference on Software and Computer Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W136741500","https://openalex.org/W1604644367","https://openalex.org/W1607035479","https://openalex.org/W2107598941","https://openalex.org/W2123442489","https://openalex.org/W2251135946","https://openalex.org/W2515462165","https://openalex.org/W2531563875","https://openalex.org/W2597601064","https://openalex.org/W2607303097","https://openalex.org/W2740759433","https://openalex.org/W2765666491","https://openalex.org/W2889224519","https://openalex.org/W2890187992","https://openalex.org/W2891417293","https://openalex.org/W2892316911","https://openalex.org/W2905524128","https://openalex.org/W2917458986","https://openalex.org/W2951274974","https://openalex.org/W2962946486","https://openalex.org/W2963014179","https://openalex.org/W2963175158","https://openalex.org/W2963912690","https://openalex.org/W2981341912","https://openalex.org/W3101707147"],"related_works":["https://openalex.org/W3013050996","https://openalex.org/W2987616634","https://openalex.org/W4385567471","https://openalex.org/W2050478393","https://openalex.org/W3211319105","https://openalex.org/W4213472049","https://openalex.org/W3015426011","https://openalex.org/W4300772098","https://openalex.org/W2098784136","https://openalex.org/W4383877521"],"abstract_inverted_index":{"Distant":[0],"supervision":[1,57],"Relation":[2],"Extraction(RE)":[3],"aligns":[4],"entities":[5],"in":[6,25,44,68,84,132],"a":[7,54,90],"Knowledge":[8],"Base":[9],"(KB)":[10],"with":[11,112],"text":[12],"to":[13,60,95],"automatically":[14],"construct":[15],"large-labeled":[16],"corpus,":[17],"which":[18],"alleviates":[19],"the":[20,37,45,69,73,78,82,85,97,109,117,122,133],"need":[21],"for":[22],"manual":[23],"annotation":[24],"traditional":[26],"RE.":[27],"However,":[28],"most":[29],"existing":[30],"models":[31,143],"can't":[32],"take":[33],"full":[34],"advantage":[35],"of":[36,41,81,128],"syntactic":[38,66,74,91,104],"structure":[39,67,92,105],"information":[40,64,111],"each":[42],"word":[43,98,124],"dependency":[46,79],"tree.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51],"propose":[52],"BGSGA,":[53],"novel":[55],"distant":[56],"RE":[58],"model,":[59],"capture":[61],"both":[62],"semantic":[63],"and":[65,87,125,130],"bag.":[70],"BGSGA":[71,139],"constructs":[72],"graph":[75],"by":[76,115],"combining":[77],"trees":[80],"sentences":[83],"bag":[86],"then":[88],"employs":[89],"attention":[93,106,119],"mechanism":[94,107],"update":[96],"embedding":[99],"obtained":[100],"from":[101],"Bi-GRU.":[102],"The":[103,135],"captures":[108],"cross-sentence":[110],"different":[113],"weight":[114],"implementing":[116],"special":[118],"operation":[120],"between":[121],"target":[123],"its":[126],"neighbors":[127],"first-order":[129],"second-order":[131],"graph.":[134],"experiments":[136],"show":[137],"that":[138],"outperforms":[140],"our":[141],"baseline":[142],"on":[144],"benchmark":[145],"datasets.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-05-13T00:00:00"}