{"id":"https://openalex.org/W2589716243","doi":"https://doi.org/10.1109/icmlc.2016.7860886","title":"SLDP: Sequence learning dependency parsing model using long short-term memory","display_name":"SLDP: Sequence learning dependency parsing model using long short-term memory","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2589716243","doi":"https://doi.org/10.1109/icmlc.2016.7860886","mag":"2589716243"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2016.7860886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2016.7860886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Machine Learning and Cybernetics (ICMLC)","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/A5052503472","display_name":"Qingyu Zhou","orcid":"https://orcid.org/0000-0002-4389-1582"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing-Yu Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000121999","display_name":"Dequan Zheng","orcid":"https://orcid.org/0000-0002-6431-360X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"De-Quan Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101661008","display_name":"Tiejun Zhao","orcid":"https://orcid.org/0000-0003-4659-4935"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tie-Jun Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052503472"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11319338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"111","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.9541714191436768},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.85894775390625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8383113145828247},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7642273902893066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7253831028938293},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.7135018110275269},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.6518409252166748},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5328282117843628},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5143262147903442},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5072783827781677},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5002186298370361},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45937952399253845},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4567711055278778},{"id":"https://openalex.org/keywords/short-term-memory","display_name":"Short-term memory","score":0.4191700220108032},{"id":"https://openalex.org/keywords/working-memory","display_name":"Working memory","score":0.10918864607810974},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.08041813969612122}],"concepts":[{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.9541714191436768},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.85894775390625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8383113145828247},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7642273902893066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7253831028938293},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7135018110275269},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.6518409252166748},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5328282117843628},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5143262147903442},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5072783827781677},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5002186298370361},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45937952399253845},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4567711055278778},{"id":"https://openalex.org/C179226034","wikidata":"https://www.wikidata.org/wiki/Q18599","display_name":"Short-term memory","level":4,"score":0.4191700220108032},{"id":"https://openalex.org/C21963081","wikidata":"https://www.wikidata.org/wiki/Q11337567","display_name":"Working memory","level":3,"score":0.10918864607810974},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.08041813969612122},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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:10.1109/icmlc.2016.7860886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2016.7860886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W140467209","https://openalex.org/W181643614","https://openalex.org/W194033037","https://openalex.org/W1508977358","https://openalex.org/W1533861849","https://openalex.org/W1591659308","https://openalex.org/W1632114991","https://openalex.org/W1815076433","https://openalex.org/W2012273848","https://openalex.org/W2022334348","https://openalex.org/W2064675550","https://openalex.org/W2068176125","https://openalex.org/W2105847779","https://openalex.org/W2114887620","https://openalex.org/W2124861326","https://openalex.org/W2147880316","https://openalex.org/W2153579005","https://openalex.org/W2161222299","https://openalex.org/W2250451826","https://openalex.org/W2250861254","https://openalex.org/W4294170691","https://openalex.org/W6605743553","https://openalex.org/W6607334719","https://openalex.org/W6607972337","https://openalex.org/W6631943919","https://openalex.org/W6635191455","https://openalex.org/W6636649193","https://openalex.org/W6638545294","https://openalex.org/W6677419442","https://openalex.org/W6678669349","https://openalex.org/W6682082992","https://openalex.org/W6682691769"],"related_works":["https://openalex.org/W2174661732","https://openalex.org/W2165926940","https://openalex.org/W1480936899","https://openalex.org/W2739717642","https://openalex.org/W2251160863","https://openalex.org/W2251128110","https://openalex.org/W2963706833","https://openalex.org/W213875708","https://openalex.org/W4297570915","https://openalex.org/W1987996389"],"abstract_inverted_index":{"Recent":[0],"work":[1],"on":[2,90],"neural":[3,32],"network":[4,33],"models":[5],"shows":[6],"success":[7],"in":[8],"dependency":[9,19,87],"parsing.":[10,88],"In":[11],"this":[12],"paper,":[13],"we":[14,52],"present":[15],"a":[16,55],"sequence":[17],"learning":[18,72],"parsing":[20,64],"(SLDP)":[21],"model":[22,39,60,67,98],"using":[23],"long":[24,56,82],"short-term":[25,57],"memory":[26,58],"for":[27,62,86],"shift-reduce":[28],"parser.":[29],"A":[30],"feed-forward":[31],"is":[34],"used":[35],"to":[36],"build":[37],"greedy":[38],"from":[40],"rich":[41],"local":[42,50],"features.":[43],"With":[44],"the":[45,49,69,81,101],"features":[46],"extracted":[47],"by":[48],"model,":[51],"further":[53],"train":[54],"(LSTM)":[59],"optimized":[61],"global":[63],"sequences.":[65],"Our":[66],"has":[68],"capability":[70],"of":[71],"not":[73],"only":[74],"atomic":[75],"feature":[76],"combinations":[77],"automatically":[78],"but":[79],"also":[80],"distance":[83],"dependent":[84],"information":[85],"Experiments":[89],"English":[91],"Penn":[92],"Treebank":[93],"show":[94],"that":[95],"our":[96],"SLDP":[97],"significantly":[99],"outperforms":[100],"baseline,":[102],"achieving":[103],"90.7%":[104],"unlabeled":[105],"attachment":[106,111],"score":[107],"and":[108],"89.0%":[109],"labeled":[110],"score.":[112]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}