Span-based relational graph transformer network for aspect–opinion pair extraction
Aspect extraction and opinion extraction are two fundamental subtasks in aspect-based sentiment analysis. Many methods extract aspect terms or opinion terms but ignore the relationships between them. However, such relationships are crucial for downstream tasks, such as sentiment classification and c...
Uložené v:
| Vydané v: | Knowledge and information systems Ročník 64; číslo 5; s. 1305 - 1322 |
|---|---|
| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
London
Springer London
01.05.2022
Springer Nature B.V |
| Predmet: | |
| ISSN: | 0219-1377, 0219-3116 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Aspect extraction and opinion extraction are two fundamental subtasks in aspect-based sentiment analysis. Many methods extract aspect terms or opinion terms but ignore the relationships between them. However, such relationships are crucial for downstream tasks, such as sentiment classification and commodity recommendation. Recently, methods have been proposed to extract both terms jointly; however, they fail to extract them as pairs. In this paper, we explore the aspect–opinion pair extraction task that aims to extract aspect and opinion terms in pairs. To carry out this task, we propose a span-based relational graph transformer network that consists of a span generator, a span classifier, and a relation detector. The span generator enumerates all possible spans to generate the candidates for aspect or opinion terms and filters non-aspects or non-opinions terms, while the relation classifier extracts aspect–opinion pairs. We propose a relational graph convolutional network to capture the dependent relationships between aspect and opinion terms. Extensive experiments show that the proposed model achieves the state-of-the-art performance using four benchmark datasets. |
|---|---|
| AbstractList | Aspect extraction and opinion extraction are two fundamental subtasks in aspect-based sentiment analysis. Many methods extract aspect terms or opinion terms but ignore the relationships between them. However, such relationships are crucial for downstream tasks, such as sentiment classification and commodity recommendation. Recently, methods have been proposed to extract both terms jointly; however, they fail to extract them as pairs. In this paper, we explore the aspect–opinion pair extraction task that aims to extract aspect and opinion terms in pairs. To carry out this task, we propose a span-based relational graph transformer network that consists of a span generator, a span classifier, and a relation detector. The span generator enumerates all possible spans to generate the candidates for aspect or opinion terms and filters non-aspects or non-opinions terms, while the relation classifier extracts aspect–opinion pairs. We propose a relational graph convolutional network to capture the dependent relationships between aspect and opinion terms. Extensive experiments show that the proposed model achieves the state-of-the-art performance using four benchmark datasets. |
| Author | Wang, Chaoqiang Lin, Yongdong Li, You Lin, Yuming Chang, Liang |
| Author_xml | – sequence: 1 givenname: You surname: Li fullname: Li, You organization: Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology – sequence: 2 givenname: Chaoqiang surname: Wang fullname: Wang, Chaoqiang organization: Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology – sequence: 3 givenname: Yuming orcidid: 0000-0001-6850-5222 surname: Lin fullname: Lin, Yuming email: ymlin@guet.edu.cn organization: Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology – sequence: 4 givenname: Yongdong surname: Lin fullname: Lin, Yongdong organization: Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology – sequence: 5 givenname: Liang surname: Chang fullname: Chang, Liang organization: Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology |
| BookMark | eNp9kE1OwzAQhS1UJNrCBVhFYh3w2IntLFHFn1SJBWVtOc6kpKRJsFMBO-7ADTkJblMJiUVXMyO97-nNm5BR0zZIyDnQS6BUXnmgAGlMGYspCJnG6oiMKYMs5gBitN-BS3lCJt6vKAUpAMZk8dSZJs6NxyJyWJu-ahtTR0tnupeod6bxZevW6KIG-_fWvUbhjIzv0PY_X99tVzUBiDpTuQg_gt5uDU7JcWlqj2f7OSXPtzeL2X08f7x7mF3PY8sh62OblKq0KCxDa7ilJWTcFiZloEpkmMsUOFKpchSJ4iFy-LTgaZbwIhcqTfiUXAy-nWvfNuh7vWo3LuT3mgnBFc2YkEGlBpV1rfcOS22rfvdoyFvVGqjeOuuhQx061LsOtQoo-4d2rlob93kY4gPkg7hZovtLdYD6Ba51h9U |
| CitedBy_id | crossref_primary_10_1007_s10844_023_00811_2 crossref_primary_10_1109_ACCESS_2025_3555744 crossref_primary_10_1007_s10115_024_02313_1 crossref_primary_10_1007_s10462_024_10906_z |
| Cites_doi | 10.1109/MIS.2016.31 10.1162/coli_a_00034 10.1142/S0218488520500294 10.1109/TKDE.2014.2339850 10.1016/j.inffus.2018.03.007 10.2200/S00416ED1V01Y201204HLT016 10.1016/j.knosys.2021.107643 10.1007/s12559-021-09948-0 10.1016/j.neucom.2021.09.057 10.1109/TASLP.2018.2875170 10.18653/v1/2020.acl-main.582 10.18653/v1/P18-1202 10.18653/v1/P19-1051 10.18653/v1/S16-1174 10.18653/v1/2020.emnlp-main.719 10.1609/aaai.v34i05.6469 10.1609/aaai.v31i1.10974 10.18653/v1/D19-1466 10.18653/v1/2020.acl-main.296 10.18653/v1/2020.coling-main.158 10.18653/v1/D15-1168 10.1145/3340531.3412003 10.3115/v1/S14-2004 10.18653/v1/P17-1036 10.1109/HICSS.2016.144 10.3115/v1/P14-1030 10.18653/v1/N19-1259 10.18653/v1/P18-2094 10.18653/v1/2020.findings-emnlp.234 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 – notice: The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. |
| DBID | AAYXX CITATION 3V. 7SC 7WY 7WZ 7XB 87Z 8AL 8AO 8FD 8FE 8FG 8FK 8FL ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L7M L~C L~D M0C M0N P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS Q9U |
| DOI | 10.1007/s10115-022-01675-8 |
| DatabaseName | CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One ProQuest Central Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Global Computing Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic ProQuest One Academic Middle East (New) ProQuest One Business (UW System Shared) ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic |
| DatabaseTitle | CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Pharma Collection ProQuest Central China ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest One Applied & Life Sciences ProQuest Central Korea ProQuest Central (New) Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Business (Alumni) ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New) Business Premium Collection (Alumni) |
| DatabaseTitleList | ABI/INFORM Global (Corporate) |
| Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 0219-3116 |
| EndPage | 1322 |
| ExternalDocumentID | 10_1007_s10115_022_01675_8 |
| GrantInformation_xml | – fundername: National Natural Science Foundation of China grantid: 61966009 funderid: http://dx.doi.org/10.13039/501100001809 – fundername: Natural Science Foundation of Guangxi Province grantid: 2020GXNSFAA159012; 2018GXNSFDA281049 funderid: http://dx.doi.org/10.13039/501100004607 – fundername: National Natural Science Foundation of China grantid: U1811264; 62062027 funderid: http://dx.doi.org/10.13039/501100001809 |
| GroupedDBID | -59 -5G -BR -EM -Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 203 29L 2J2 2JN 2JY 2KG 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5VS 67Z 6KP 6NX 7WY 8AO 8FE 8FG 8FL 8FW 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACGFO ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACREN ACSNA ACZOJ ADHHG ADHIR ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEBTG AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFGCZ AFKRA AFLOW AFQWF AFWTZ AFYQB AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 DWQXO EBLON EBS EDO EIOEI EJD ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I-F I09 IHE IJ- IKXTQ ITM IWAJR IXC IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K60 K6V K6~ K7- KDC KOV LAS LLZTM M0C M0N M4Y MA- MK~ ML~ N2Q NB0 NPVJJ NQJWS NU0 O9- O93 O9J OAM P2P P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PT4 PT5 Q2X QOS R89 R9I RIG ROL RPX RSV S16 S1Z S27 S3B SAP SCO SDH SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z5O Z7R Z7S Z7X Z7Y Z7Z Z81 Z83 Z88 ZMTXR ~A9 AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PQGLB 7SC 7XB 8AL 8FD 8FK JQ2 L.- L7M L~C L~D PKEHL PQEST PQUKI PRINS Q9U |
| ID | FETCH-LOGICAL-c319t-c4f8fce6c2eca3c0f193cda5218fe2eb7513e078be6483001007d35943db68543 |
| IEDL.DBID | K7- |
| ISICitedReferencesCount | 5 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000781256500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0219-1377 |
| IngestDate | Sat Nov 08 14:36:57 EST 2025 Sat Nov 29 02:29:25 EST 2025 Tue Nov 18 20:55:01 EST 2025 Fri Feb 21 02:47:25 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 5 |
| Keywords | Sentiment analysis Relational graph convolution Aspect–opinion pair extraction |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c319t-c4f8fce6c2eca3c0f193cda5218fe2eb7513e078be6483001007d35943db68543 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0001-6850-5222 |
| PQID | 2663809267 |
| PQPubID | 43394 |
| PageCount | 18 |
| ParticipantIDs | proquest_journals_2663809267 crossref_citationtrail_10_1007_s10115_022_01675_8 crossref_primary_10_1007_s10115_022_01675_8 springer_journals_10_1007_s10115_022_01675_8 |
| PublicationCentury | 2000 |
| PublicationDate | 20220500 2022-05-00 20220501 |
| PublicationDateYYYYMMDD | 2022-05-01 |
| PublicationDate_xml | – month: 5 year: 2022 text: 20220500 |
| PublicationDecade | 2020 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London |
| PublicationSubtitle | An International Journal |
| PublicationTitle | Knowledge and information systems |
| PublicationTitleAbbrev | Knowl Inf Syst |
| PublicationYear | 2022 |
| Publisher | Springer London Springer Nature B.V |
| Publisher_xml | – name: Springer London – name: Springer Nature B.V |
| References | Liu, Xu, Zhao (CR3) 2015; 27 Kumar, Trueman, Cambria (CR20) 2021; 13 CR17 CR16 CR15 Liu (CR18) 2012; 5 CR14 Wang, Ho, Cambria (CR22) 2020; 28 CR13 Li, Shao, Ji, Cambria (CR24) 2022; 467 CR34 CR11 CR33 CR10 Yu, Jiang, Xia (CR12) 2019; 27 CR32 CR31 CR30 CR2 Valdivia, Luzón, Cambria, Herrera (CR21) 2018; 44 CR4 CR6 CR5 CR8 CR7 Liang, Su, Gui, Cambria, Xu (CR19) 2022; 235 CR28 CR9 CR27 CR26 CR25 CR23 Cambria (CR1) 2016; 31 Qiu, Liu, Bu (CR29) 2011; 37 K Liu (1675_CR3) 2015; 27 1675_CR16 1675_CR17 1675_CR10 B Liang (1675_CR19) 2022; 235 1675_CR32 1675_CR11 1675_CR33 1675_CR30 E Cambria (1675_CR1) 2016; 31 1675_CR31 1675_CR14 G Qiu (1675_CR29) 2011; 37 1675_CR15 J Yu (1675_CR12) 2019; 27 1675_CR34 1675_CR13 W Li (1675_CR24) 2022; 467 Z Wang (1675_CR22) 2020; 28 1675_CR27 1675_CR28 1675_CR6 AJ Kumar (1675_CR20) 2021; 13 1675_CR5 B Liu (1675_CR18) 2012; 5 1675_CR4 1675_CR25 1675_CR9 1675_CR26 1675_CR8 1675_CR23 1675_CR7 A Valdivia (1675_CR21) 2018; 44 1675_CR2 |
| References_xml | – volume: 31 start-page: 102 issue: 2 year: 2016 end-page: 107 ident: CR1 article-title: Affect computing and sentiment analysis publication-title: IEEE Intell Syst doi: 10.1109/MIS.2016.31 – ident: CR4 – ident: CR14 – ident: CR2 – ident: CR16 – ident: CR30 – ident: CR10 – ident: CR33 – volume: 37 start-page: 9 issue: 1 year: 2011 end-page: 27 ident: CR29 article-title: Opinion word expansion and target extraction through double propagation publication-title: Comput Linguist doi: 10.1162/coli_a_00034 – ident: CR6 – ident: CR8 – ident: CR25 – ident: CR27 – volume: 28 start-page: 683 issue: 4 year: 2020 end-page: 697 ident: CR22 article-title: Multi-level fine-scaled sentiment sensing with ambivalence handling publication-title: Int J Uncertain Fuzziness Knowl Based Syst doi: 10.1142/S0218488520500294 – ident: CR23 – volume: 27 start-page: 636 issue: 3 year: 2015 end-page: 650 ident: CR3 article-title: Co-extracting opinion targets and opinion words from online reviews based on the word alignment model publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2014.2339850 – volume: 44 start-page: 126 year: 2018 end-page: 135 ident: CR21 article-title: Consensus vote models for detecting and filtering neutrality in sentiment analysis publication-title: Inf Fusion doi: 10.1016/j.inffus.2018.03.007 – volume: 5 start-page: 1 issue: 1 year: 2012 end-page: 167 ident: CR18 article-title: Sentiment analysis and opinion mining publication-title: Synth Lect Hum Lang Technol doi: 10.2200/S00416ED1V01Y201204HLT016 – ident: CR15 – ident: CR17 – ident: CR31 – ident: CR13 – ident: CR11 – ident: CR9 – volume: 235 start-page: 107643 year: 2022 ident: CR19 article-title: Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional network publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2021.107643 – ident: CR32 – ident: CR34 – volume: 13 start-page: 1423 year: 2021 end-page: 1432 ident: CR20 article-title: A convolutional stacked bidirectional LSTM with a multiplicative attention mechanism for aspect category and sentiment detection publication-title: Cogn Comput doi: 10.1007/s12559-021-09948-0 – ident: CR5 – volume: 467 start-page: 73 year: 2022 end-page: 82 ident: CR24 article-title: BiERU: bidirectional emotional recurrent unit for conversational sentiment analysis publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.09.057 – ident: CR7 – ident: CR28 – volume: 27 start-page: 168 issue: 1 year: 2019 end-page: 177 ident: CR12 article-title: Global inference for aspect and opinion terms co-extraction based on multi-task neural networks publication-title: IEEE/ACM Trans Audio Speech Lang Process doi: 10.1109/TASLP.2018.2875170 – ident: CR26 – ident: 1675_CR30 doi: 10.18653/v1/2020.acl-main.582 – ident: 1675_CR11 doi: 10.18653/v1/P18-1202 – ident: 1675_CR16 doi: 10.18653/v1/P19-1051 – volume: 28 start-page: 683 issue: 4 year: 2020 ident: 1675_CR22 publication-title: Int J Uncertain Fuzziness Knowl Based Syst doi: 10.1142/S0218488520500294 – ident: 1675_CR26 doi: 10.18653/v1/S16-1174 – ident: 1675_CR8 doi: 10.18653/v1/2020.emnlp-main.719 – ident: 1675_CR7 doi: 10.1609/aaai.v34i05.6469 – ident: 1675_CR13 doi: 10.1609/aaai.v31i1.10974 – ident: 1675_CR27 – ident: 1675_CR31 doi: 10.18653/v1/D19-1466 – ident: 1675_CR14 doi: 10.18653/v1/2020.acl-main.296 – volume: 37 start-page: 9 issue: 1 year: 2011 ident: 1675_CR29 publication-title: Comput Linguist doi: 10.1162/coli_a_00034 – ident: 1675_CR10 doi: 10.18653/v1/2020.coling-main.158 – ident: 1675_CR33 – ident: 1675_CR9 doi: 10.18653/v1/D15-1168 – volume: 5 start-page: 1 issue: 1 year: 2012 ident: 1675_CR18 publication-title: Synth Lect Hum Lang Technol doi: 10.2200/S00416ED1V01Y201204HLT016 – ident: 1675_CR23 doi: 10.1145/3340531.3412003 – volume: 13 start-page: 1423 year: 2021 ident: 1675_CR20 publication-title: Cogn Comput doi: 10.1007/s12559-021-09948-0 – volume: 235 start-page: 107643 year: 2022 ident: 1675_CR19 publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2021.107643 – volume: 467 start-page: 73 year: 2022 ident: 1675_CR24 publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.09.057 – ident: 1675_CR2 doi: 10.3115/v1/S14-2004 – volume: 27 start-page: 168 issue: 1 year: 2019 ident: 1675_CR12 publication-title: IEEE/ACM Trans Audio Speech Lang Process doi: 10.1109/TASLP.2018.2875170 – ident: 1675_CR28 – ident: 1675_CR4 doi: 10.18653/v1/P17-1036 – ident: 1675_CR15 doi: 10.1109/HICSS.2016.144 – ident: 1675_CR25 doi: 10.3115/v1/P14-1030 – volume: 31 start-page: 102 issue: 2 year: 2016 ident: 1675_CR1 publication-title: IEEE Intell Syst doi: 10.1109/MIS.2016.31 – ident: 1675_CR32 – ident: 1675_CR6 doi: 10.18653/v1/N19-1259 – ident: 1675_CR34 – volume: 27 start-page: 636 issue: 3 year: 2015 ident: 1675_CR3 publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2014.2339850 – ident: 1675_CR5 doi: 10.18653/v1/P18-2094 – ident: 1675_CR17 doi: 10.18653/v1/2020.findings-emnlp.234 – volume: 44 start-page: 126 year: 2018 ident: 1675_CR21 publication-title: Inf Fusion doi: 10.1016/j.inffus.2018.03.007 |
| SSID | ssj0017611 |
| Score | 2.3182423 |
| Snippet | Aspect extraction and opinion extraction are two fundamental subtasks in aspect-based sentiment analysis. Many methods extract aspect terms or opinion terms... |
| SourceID | proquest crossref springer |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1305 |
| SubjectTerms | Classifiers Computer Science Data mining Data Mining and Knowledge Discovery Database Management Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) IT in Business Recommender systems Regular Paper Sentiment analysis Transformers |
| SummonAdditionalLinks | – databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1NS8QwEB109eDF9RNXV8nBmwbaJm3To4iLB1nEXWVvJU1TWJAq3erZ_-A_9Jc4SdNdFRX0WJoJZZLJeyUzbwCOPURhiVuFBkGSUS60pEKGBZUhD2TBIjSzIq5X8XAoJpPk2hWFzdps9_ZK0p7UH4rdkL1Qk31uUudDKpZhBeFOmHC8Gd3N7w7wx9z2ycNYpEZPz5XKfD_HZzhacMwv16IWbQbd_33nBqw7dknOmu2wCUu63IJu27mBuEDehvEIDwFqECwnlUuHQzurXk3qlsuiRdlkiRN8JNJWZb69vJoaKzQgj3JaETzcq6Y4YgduBxfj80vq-itQhYFXU8ULUSgdqUAryZRXIJlTuURAF4UOdBaHPtNIITIdccHM36MX5yxMOMuzSISc7UKnfCj1HhCdGVGfHKGuYFzmOEGRCy0yLjKfa9_rgd-6OVVOfNz0wLhPF7LJxm0pui21bktFD07mNo-N9Mavo_vt6qUuDGcpsg8mvCSI4h6ctqu1eP3zbPt_G34Aa4FdcJMI2YdOXT3pQ1hVz_V0Vh3Z7fkOXNPfXg priority: 102 providerName: Springer Nature |
| Title | Span-based relational graph transformer network for aspect–opinion pair extraction |
| URI | https://link.springer.com/article/10.1007/s10115-022-01675-8 https://www.proquest.com/docview/2663809267 |
| Volume | 64 |
| WOSCitedRecordID | wos000781256500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 0219-3116 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017611 issn: 0219-1377 databaseCode: RSV dateStart: 19990201 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEB7U9eDFt7g-lhy8abBN0jZ7EpVdBHVZfOulpGkKgqxrd_Xsf_Af-kucZNNdFPTiJVDaCSXzTDLzDcBOgF5YoahQxpoZFdIoKlVUUBUJpgoeI5kDcT1LOh15d9fs-gO3gU-rrGyiM9T5s7Zn5PvoSLgMmixODvov1HaNsrervoXGNNRCxkIr56cJHd8i4BbddcxDraQWWc8XzfjSOYyFqM1lt4n4EZXfHdMk2vxxQer8Tnvhv3-8CPM-4iSHIxFZginTW4aFqpsD8cq9AleXaBio9Wo5KX2KHNI5RGsyrOJbpOiNMscJPhLlKjU_3z9s3RUSkL56LAka_HJUMLEK1-3W1fEJ9T0XqEZlHFItClloE2tmtOI6KDDA07lCJy8Lw0yWRCE3GFZkJhaS2x1lkOQ8agqeZ7GMBF-Dmd5zz6wDMZkF-snR_RVcqBwnKHJpZCZkFgoTBnUIqwVPtQckt30xntIJlLJlUopMSh2TUlmH3TFNfwTH8efXWxVnUq-ag3TCljrsVbydvP59to2_Z9uEOebEySZDbsHMsHw12zCr34aPg7IB08ntfQNqR61O96LhxBTH8-AYx270gOPF5c0XQ4Hu2Q |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LS8QwEB58gV58i-szBz1psJukbXoQER8orovgCt5qmqawIOvaXRVv_gf_hz_KX-IkbV0U9ObBY2lnoM2X-SadF8CGhyysECqUsSihQhpFpfIzqnzBVMYDFHNNXBthsymvr6OLIXiramFsWmVlE52hTu-0_Ue-g0TCpRexINzr3lM7NcpGV6sRGgUszszzEx7Zerunh7i-m4wdH7UOTmg5VYBqhFufapHJTJtAM6MV116GLoxOFdKYzAwzSejXuUHiTEwgJLdnJi9MuR8JniaB9AVHvcMwKgRuB5sq6B18Ri3CwM37RdqMqO3kVxbplKV66HtRmztvE_99Kr8S4cC7_RaQdTx3PPXfvtA0TJYeNdkvtsAMDJnOLExV0ypIabzmoHWJho9a1k5JXqYAopzr2E36lf-OEp0iM57gJVGuEvX95dXWlaEA6ap2TpDQ8qIgZB6u_uTdFmCkc9cxi0BMYhsZpUjvGRcqRQVZKo1MhEzqwtS9GtSrBY512XDdzv24jQetoi0oYgRF7EARyxpsfcp0i3Yjvz69UiEhLk1PLx7AoAbbFZYGt3_WtvS7tnUYP2mdN-LGafNsGSaYg7JN_FyBkX7-YFZhTD_22718zW0KAjd_jbEPWNBF8g |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3NTtwwEB4BRYgLlD91gRYf4AQWWdtJnENVIeiqCLRaCZAQl-A4trRStSzZbRE33oG34XH6JB07DisqlRsHjlEyIyX-PN9MPD8A2xGysEKoUMayggppFJUqtlTFginLExTzTVxP025XXl5mvSl4amphXFplYxO9oS5vtPtHvo9EwmWUsSTdtyEtonfU-Ta8pW6ClDtpbcZp1BA5Mfd3GL6Nvh4f4VrvMNb5fn74g4YJA1Qj9MZUCyutNolmRiuuI4vujC4VUpq0hpkijdvcIIkWJhGSu_gpSkseZ4KXRSJjwVHvNHxIMcZ0gV8vvno-wUgTP_sXKTSjrqtfKNgJZXvoh1GXR--KAGIqX5LixNP953DWc15n8T1_rY-wEDxtclBvjSWYMoNlWGymWJBg1Fbg_AwNInVsXpIqpAainO_kTcaNX48SgzpjnuAlUb5C9c_Do6s3QwEyVP2K4PtXdaHIKly8ybutwczgZmA-ATGFa3BUIu1bLlSJCmwpjSyELNrCtKMWtJvFznVoxO7mgfzMJy2kHUByBEjuAZLLFuw-ywzrNiSvPr3ZoCIPJmmUTyDRgr0GV5Pb_9e2_rq2LZhDaOWnx92TDZhnHtUuH3QTZsbVL_MZZvXvcX9UffH7g8D1W0PsLwpbTwM |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Span-based+relational+graph+transformer+network+for+aspect%E2%80%93opinion+pair+extraction&rft.jtitle=Knowledge+and+information+systems&rft.au=Li%2C+You&rft.au=Wang%2C+Chaoqiang&rft.au=Lin%2C+Yuming&rft.au=Lin%2C+Yongdong&rft.date=2022-05-01&rft.issn=0219-1377&rft.eissn=0219-3116&rft.volume=64&rft.issue=5&rft.spage=1305&rft.epage=1322&rft_id=info:doi/10.1007%2Fs10115-022-01675-8&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s10115_022_01675_8 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0219-1377&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0219-1377&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0219-1377&client=summon |