{"id":"https://openalex.org/W3119919975","doi":"https://doi.org/10.1109/ialp51396.2020.9310511","title":"Sentiment classification with syntactic relationship and attention for teaching evaluation texts","display_name":"Sentiment classification with syntactic relationship and attention for teaching evaluation texts","publication_year":2020,"publication_date":"2020-12-04","ids":{"openalex":"https://openalex.org/W3119919975","doi":"https://doi.org/10.1109/ialp51396.2020.9310511","mag":"3119919975"},"language":"en","primary_location":{"id":"doi:10.1109/ialp51396.2020.9310511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp51396.2020.9310511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5083881203","display_name":"Lingling Mu","orcid":"https://orcid.org/0000-0001-6556-784X"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Mu","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101487701","display_name":"Yadi Li","orcid":"https://orcid.org/0000-0002-1553-7922"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadi Li","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062969664","display_name":"Hongying Zan","orcid":"https://orcid.org/0000-0002-8874-1262"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongying Zan","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, P.R.China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"270","last_page":"275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10028","display_name":"Topic Modeling","score":0.9940000176429749,"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":0.9835000038146973,"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":0.8429563045501709},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.7410383820533752},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6845789551734924},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6772816181182861},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6568384170532227},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5712422728538513},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5619462132453918},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.23198682069778442}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8429563045501709},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.7410383820533752},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6845789551734924},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6772816181182861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6568384170532227},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5712422728538513},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5619462132453918},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.23198682069778442},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ialp51396.2020.9310511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp51396.2020.9310511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8600000143051147}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2064675550","https://openalex.org/W2157331557","https://openalex.org/W2407776548","https://openalex.org/W2517194566","https://openalex.org/W2606788537","https://openalex.org/W2739774142","https://openalex.org/W2899723212"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829"],"abstract_inverted_index":{"In":[0,100],"this":[1,101,156],"paper,":[2],"teaching":[3,16,25,83,135,162,176],"evaluation":[4,9,17,26,84,136,163,177],"refers":[5],"to":[6,55],"the":[7,15,22,30,56,103,111,122,134,149,159,173],"students'":[8],"of":[10,24,106,118,133,152,161,175],"teaching.":[11],"To":[12],"help":[13],"complete":[14,29],"work":[18],"better,":[19],"we":[20],"construct":[21],"corpus":[23,36],"texts":[27,53,63,85,137,164],"and":[28,42,73,89],"sentiment":[31,79,131],"classification":[32,80,132,150],"on":[33,87,158],"it.":[34],"The":[35,49,116,130,144],"is":[37,138,165],"collected":[38],"from":[39],"a":[40,78,141],"university":[41],"processed,":[43],"which":[44,69,167],"includes":[45],"10,299":[46],"Chinese":[47],"sentences.":[48],"annotators":[50],"manually":[51],"label":[52],"according":[54],"rules":[57],"designed":[58],"by":[59,140],"educational":[60],"experts.":[61],"These":[62],"are":[64,70,108,124],"divided":[65],"into":[66,110],"three":[67],"categories,":[68],"positive,":[71],"negative,":[72],"neutral.":[74],"This":[75],"paper":[76,157],"proposes":[77],"method":[81],"for":[82,113],"based":[86],"Attention":[88],"BiLSTM":[90,112],"(Bi-directional":[91],"Long":[92],"Short-Term":[93],"Memory)":[94],"combined":[95],"with":[96],"Syntactic":[97],"Relationships":[98],"(BLASR).":[99],"model,":[102],"syntactic":[104],"relationships":[105],"sentences":[107,123],"fused":[109],"feature":[114],"learning.":[115],"weights":[117],"different":[119],"words":[120],"in":[121,155,178],"calculated":[125],"through":[126],"an":[127],"attention":[128],"layer.":[129,143],"completed":[139],"dense":[142],"experimental":[145],"results":[146],"show":[147],"that":[148],"accuracy":[151],"BLASR":[153],"proposed":[154],"dataset":[160],"89.04%,":[166],"outperforms":[168],"baselines.":[169],"It":[170],"can":[171],"satisfy":[172],"needs":[174],"colleges.":[179]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
