{"id":"https://openalex.org/W2252007242","doi":"https://doi.org/10.18653/v1/d15-1073","title":"Neural Networks for Open Domain Targeted Sentiment","display_name":"Neural Networks for Open Domain Targeted Sentiment","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2252007242","doi":"https://doi.org/10.18653/v1/d15-1073","mag":"2252007242"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d15-1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1073","pdf_url":"https://www.aclweb.org/anthology/D15-1073.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 2015 Conference on Empirical Methods in Natural Language Processing","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/D15-1073.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004953265","display_name":"Meishan Zhang","orcid":"https://orcid.org/0000-0001-6335-1340"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Meishan Zhang","raw_affiliation_strings":["Singapore University of Technology and Design"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333729","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0002-5214-2268"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["Singapore University of Technology and Design"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073295657","display_name":"Duy Tin Vo","orcid":null},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Duy Tin Vo","raw_affiliation_strings":["Singapore University of Technology and Design"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I152815399"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":247,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"612","last_page":"621"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/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":0.9980000257492065,"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":0.6631274223327637},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5598886609077454},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5310654640197754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4416045844554901},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.42851829528808594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12737134099006653}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6631274223327637},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5598886609077454},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5310654640197754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4416045844554901},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.42851829528808594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12737134099006653},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/d15-1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1073","pdf_url":"https://www.aclweb.org/anthology/D15-1073.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.3911","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.3911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D15/D15-1073.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/d15-1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1073","pdf_url":"https://www.aclweb.org/anthology/D15-1073.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320324110","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2252007242.pdf","grobid_xml":"https://content.openalex.org/works/W2252007242.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W35527955","https://openalex.org/W50799546","https://openalex.org/W71795751","https://openalex.org/W1517771839","https://openalex.org/W1575907248","https://openalex.org/W1859957297","https://openalex.org/W2014902591","https://openalex.org/W2056894934","https://openalex.org/W2081375810","https://openalex.org/W2100362224","https://openalex.org/W2113125055","https://openalex.org/W2114016557","https://openalex.org/W2115834228","https://openalex.org/W2120615054","https://openalex.org/W2121227244","https://openalex.org/W2126131681","https://openalex.org/W2126854223","https://openalex.org/W2134033474","https://openalex.org/W2146502635","https://openalex.org/W2155169782","https://openalex.org/W2157807817","https://openalex.org/W2158139315","https://openalex.org/W2158899491","https://openalex.org/W2160097208","https://openalex.org/W2160660844","https://openalex.org/W2170414372","https://openalex.org/W2226111737","https://openalex.org/W2250553586","https://openalex.org/W2251124635","https://openalex.org/W2251223265","https://openalex.org/W2251900677","https://openalex.org/W2251939518","https://openalex.org/W2251951623","https://openalex.org/W2252215182","https://openalex.org/W2296071000","https://openalex.org/W2952230511","https://openalex.org/W4248506559","https://openalex.org/W4251260102"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2539940768","https://openalex.org/W2578140855","https://openalex.org/W3105313172","https://openalex.org/W4296474753","https://openalex.org/W4234387670","https://openalex.org/W2286186409"],"abstract_inverted_index":{"Open":[0],"domain":[1],"targeted":[2],"sentiment":[3,17,72],"is":[4,27],"the":[5,16,46,56,77,87],"joint":[6],"information":[7],"extraction":[8],"task":[9,26,57],"that":[10,76],"finds":[11],"target":[12],"mentions":[13],"together":[14],"with":[15],"towards":[18],"each":[19],"mention":[20],"from":[21],"a":[22,31,60,93],"text":[23],"corpus.":[24],"The":[25],"typically":[28],"modeled":[29],"as":[30,41],"sequence":[32],"labeling":[33],"problem,":[34],"and":[35,51,98],"solved":[36],"using":[37,63],"state-of-the-art":[38],"labelers":[39],"such":[40],"CRF.":[42],"We":[43],"empirically":[44],"study":[45],"effect":[47],"of":[48,96],"word":[49],"embeddings":[50],"automatic":[52],"feature":[53],"combinations":[54],"on":[55],"by":[58,84],"extending":[59],"CRF":[61],"baseline":[62],"neural":[64,78,97],"networks,":[65],"which":[66,101],"have":[67],"demonstrated":[68],"large":[69],"potentials":[70],"for":[71],"analysis.":[73],"Results":[74],"show":[75],"model":[79],"can":[80],"give":[81],"better":[82],"results":[83,110],"significantly":[85,108],"increasing":[86],"recall.":[88],"In":[89],"addition,":[90],"we":[91],"propose":[92],"novel":[94],"integration":[95],"discrete":[99],"features,":[100],"combines":[102],"their":[103],"relative":[104],"advantages,":[105],"leading":[106],"to":[107,112],"higher":[109],"compared":[111],"both":[113],"baselines.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":57},{"year":2019,"cited_by_count":33},{"year":2018,"cited_by_count":20},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":14}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
