{"id":"https://openalex.org/W2178551064","doi":"https://doi.org/10.3115/v1/s14-2107","title":"SZTE-NLP: Aspect level opinion mining exploiting syntactic cues","display_name":"SZTE-NLP: Aspect level opinion mining exploiting syntactic cues","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2178551064","doi":"https://doi.org/10.3115/v1/s14-2107","mag":"2178551064"},"language":"en","primary_location":{"id":"doi:10.3115/v1/s14-2107","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/s14-2107","pdf_url":"https://doi.org/10.3115/v1/s14-2107","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3115/v1/s14-2107","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090950630","display_name":"Viktor Hangya","orcid":"https://orcid.org/0000-0002-5144-3069"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Viktor Hangya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020987552","display_name":"G\u00e1bor Berend","orcid":"https://orcid.org/0000-0002-3845-4978"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gabor Berend","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059315217","display_name":"Istv\u00e1n Varga","orcid":"https://orcid.org/0000-0002-5727-9415"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Istv\u00e1n Varga","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5076395593","display_name":"Rich\u00e1rd Farkas","orcid":"https://orcid.org/0000-0001-7019-2632"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rich\u00e1rd Farkas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"610","last_page":"614"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9993000030517578,"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":0.9958999752998352,"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":0.8816050291061401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8206424713134766},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7736426591873169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7552227973937988},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.73405921459198},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.7221712470054626},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7146334648132324},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.662445068359375},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6589567065238953},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.6185126900672913},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5627449154853821},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.489866703748703},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4264102280139923},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.41843071579933167},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2119118869304657},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12343129515647888}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.8816050291061401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8206424713134766},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7736426591873169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7552227973937988},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.73405921459198},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7221712470054626},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7146334648132324},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.662445068359375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6589567065238953},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.6185126900672913},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5627449154853821},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.489866703748703},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4264102280139923},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.41843071579933167},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2119118869304657},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12343129515647888},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3115/v1/s14-2107","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/s14-2107","pdf_url":"https://doi.org/10.3115/v1/s14-2107","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)","raw_type":"proceedings-article"},{"id":"pmh:oai:publicatio.bibl.u-szeged.hu:7731","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400675","display_name":"SZTE Publicatio Repozit\u00f3rium (University of Szeged)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I227486990","host_organization_name":"University of Szeged","host_organization_lineage":["https://openalex.org/I227486990"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"K\u00f6nyv r\u00e9sze"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.710.3339","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.710.3339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://alt.qcri.org/semeval2014/cdrom/pdf/SemEval107.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/s14-2107","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/s14-2107","pdf_url":"https://doi.org/10.3115/v1/s14-2107","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W183066880","https://openalex.org/W193524605","https://openalex.org/W1978588883","https://openalex.org/W2097606805","https://openalex.org/W2106477703","https://openalex.org/W2169615869","https://openalex.org/W2251648804"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W2117643817","https://openalex.org/W1984947604","https://openalex.org/W2005486303","https://openalex.org/W1517853909","https://openalex.org/W3116094929","https://openalex.org/W2146338426","https://openalex.org/W3113780774","https://openalex.org/W3080107585","https://openalex.org/W3101763502"],"abstract_inverted_index":{"In":[0],"this":[1,51],"paper,":[2],"we":[3,53],"introduce":[4],"our":[5],"contribu-tions":[6],"to":[7,34,38],"the":[8,25,31],"SemEval-2014":[9],"Task":[10],"4":[11],"\u2013":[12],"As-pect":[13],"Based":[14],"Sentiment":[15],"Analysis":[16],"(Pontiki":[17],"et":[18],"al.,":[19],"2014)":[20],"challenge.":[21],"We":[22],"participated":[23],"in":[24],"aspect":[26,41],"term":[27],"polarity":[28],"subtask":[29],"where":[30],"goal":[32],"was":[33],"classify":[35],"opinions":[36],"related":[37],"a":[39,60],"given":[40],"into":[42],"positive,":[43],"negative,":[44],"neutral":[45],"or":[46],"conflict":[47],"classes.":[48],"To":[49],"solve":[50],"problem,":[52],"employed":[54],"supervised":[55],"ma-chine":[56],"learning":[57],"techniques":[58],"exploiting":[59],"rich":[61],"feature":[62,65],"set.":[63],"Our":[64],"templates":[66],"ex-ploited":[67],"both":[68],"phrase":[69],"structure":[70],"and":[71],"depen-dency":[72],"parses.":[73],"1":[74]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}