{"id":"https://openalex.org/W2473775699","doi":"https://doi.org/10.18653/v1/s16-1058","title":"ECNU at SemEval-2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect-Based Sentiment Analysis in Reviews","display_name":"ECNU at SemEval-2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect-Based Sentiment Analysis in Reviews","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2473775699","doi":"https://doi.org/10.18653/v1/s16-1058","mag":"2473775699"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s16-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1058","pdf_url":"https://www.aclweb.org/anthology/S16-1058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S16-1058.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112315754","display_name":"Mengxiao Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengxiao Jiang","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393616","display_name":"Zhihua Zhang","orcid":"https://orcid.org/0000-0003-3165-5213"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihua Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057508424","display_name":"Man Lan","orcid":"https://orcid.org/0000-0002-1423-1286"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Man Lan","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China","Shanghai Key Laboratory of Multidimensional Information Processing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, P.R.China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Shanghai Key Laboratory of Multidimensional Information Processing","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057508424"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"361","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9986000061035156,"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":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.9524441957473755},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8043904304504395},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7899867296218872},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7457784414291382},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.633813202381134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5757130980491638},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.561958909034729},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0551314651966095}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9524441957473755},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8043904304504395},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7899867296218872},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7457784414291382},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.633813202381134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5757130980491638},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.561958909034729},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0551314651966095},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s16-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1058","pdf_url":"https://www.aclweb.org/anthology/S16-1058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s16-1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1058","pdf_url":"https://www.aclweb.org/anthology/S16-1058.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4760357681","display_name":null,"funder_award_id":"14DZ2260800","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"}],"funders":[{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2473775699.pdf","grobid_xml":"https://content.openalex.org/works/W2473775699.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W185460875","https://openalex.org/W582033733","https://openalex.org/W2044429219","https://openalex.org/W2108420397","https://openalex.org/W2129294185","https://openalex.org/W2153579005","https://openalex.org/W2250225901","https://openalex.org/W2250696588","https://openalex.org/W3100922322","https://openalex.org/W4294170691","https://openalex.org/W4313037258"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W2751613946","https://openalex.org/W4287887314","https://openalex.org/W2803726945","https://openalex.org/W4291593823","https://openalex.org/W2805641541","https://openalex.org/W4385572443","https://openalex.org/W2955722679","https://openalex.org/W2963463993","https://openalex.org/W2471749924"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"our":[3],"systems":[4],"submitted":[5],"to":[6,85],"the":[7,38,52,57,89,93],"Sentence-level":[8],"and":[9,30,46,78],"Text-level":[10],"Aspect-Based":[11],"Sentiment":[12,31,70],"Analysis":[13],"(ABSA)":[14],"task":[15,22],"(i.e.,":[16,69],"Task":[17],"5)":[18],"in":[19,37,44],"SemEval-2016.":[20],"The":[21],"involves":[23],"two":[24],"phases,":[25],"namely,":[26],"Aspect":[27],"Detection":[28],"phase":[29,40],"Polarity":[32],"Classification":[33],"phase.":[34],"We":[35],"participated":[36],"second":[39],"of":[41,67],"both":[42],"subtasks":[43],"laptop":[45],"restaurant":[47],"domains,":[48],"which":[49],"focuses":[50],"on":[51,56],"sentiment":[53,102],"analysis":[54],"based":[55],"given":[58],"aspect.":[59],"In":[60],"this":[61],"task,":[62],"we":[63],"extracted":[64],"four":[65],"types":[66],"features":[68,95],"Lexicon":[71],"Features,":[72,74],"Linguistic":[73],"Topic":[75],"Model":[76],"Features":[77],"Word2vec":[79],"Feature)":[80],"from":[81],"certain":[82],"fragments":[83],"related":[84],"aspect":[86],"rather":[87],"than":[88],"whole":[90],"sentence.":[91],"Then":[92],"proposed":[94],"are":[96],"fed":[97],"into":[98],"supervised":[99],"classifiers":[100],"for":[101],"analysis.":[103],"Our":[104],"submissions":[105],"rank":[106],"above":[107],"average.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}