Joint Extraction of Entities and Relations Based on Enhanced Span and Gate Mechanism

Although entity and relation joint extraction can obtain relational triples efficiently and accurately, there are a number of problems; for instance, the information between entity relations could be transferred better, entity extraction based on span is inefficient, and it is difficult to identify...

Full description

Saved in:
Bibliographic Details
Published inApplied sciences Vol. 13; no. 19; p. 10643
Main Authors Zhang, Nan, Xin, Junfang, Cai, Qiang, Chung, Vera
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.10.2023
Subjects
Online AccessGet full text
ISSN2076-3417
2076-3417
DOI10.3390/app131910643

Cover

Abstract Although entity and relation joint extraction can obtain relational triples efficiently and accurately, there are a number of problems; for instance, the information between entity relations could be transferred better, entity extraction based on span is inefficient, and it is difficult to identify nested entities. In this paper, a joint entity and relation extraction model based on an Enhanced Span and Gate Mechanism (ESGM) is proposed to solve the above problems. We design a new span device to solve the problem of entity nesting and inefficiency. We use the pointer network method to predict the beginning and end of the span, and combine them through the one-to-many matching principle. A binary classification model is then trained to predict whether the span of the combination is the subject. In the object prediction stage, a gating unit is added to fuse the subject information with the sentence information and strengthen the information transfer between the entity and the relationship. Finally, the relationship is used as the mapping function to predict the tail entity related to the head entity. Our experimental results prove the effectiveness of this model. The precision of the proposed model reached 93.8% on the NYT dataset, which was 0.4% higher than that of the comparison model. Moreover, when the same experiment was conducted in a nested entity scenario, the accuracy of the proposed model was 4.4% higher than that of the comparison model.
AbstractList Although entity and relation joint extraction can obtain relational triples efficiently and accurately, there are a number of problems; for instance, the information between entity relations could be transferred better, entity extraction based on span is inefficient, and it is difficult to identify nested entities. In this paper, a joint entity and relation extraction model based on an Enhanced Span and Gate Mechanism (ESGM) is proposed to solve the above problems. We design a new span device to solve the problem of entity nesting and inefficiency. We use the pointer network method to predict the beginning and end of the span, and combine them through the one-to-many matching principle. A binary classification model is then trained to predict whether the span of the combination is the subject. In the object prediction stage, a gating unit is added to fuse the subject information with the sentence information and strengthen the information transfer between the entity and the relationship. Finally, the relationship is used as the mapping function to predict the tail entity related to the head entity. Our experimental results prove the effectiveness of this model. The precision of the proposed model reached 93.8% on the NYT dataset, which was 0.4% higher than that of the comparison model. Moreover, when the same experiment was conducted in a nested entity scenario, the accuracy of the proposed model was 4.4% higher than that of the comparison model.
Audience Academic
Author Chung, Vera
Xin, Junfang
Zhang, Nan
Cai, Qiang
Author_xml – sequence: 1
  givenname: Nan
  orcidid: 0000-0003-4904-7857
  surname: Zhang
  fullname: Zhang, Nan
– sequence: 2
  givenname: Junfang
  surname: Xin
  fullname: Xin, Junfang
– sequence: 3
  givenname: Qiang
  surname: Cai
  fullname: Cai, Qiang
– sequence: 4
  givenname: Vera
  orcidid: 0000-0002-3158-9650
  surname: Chung
  fullname: Chung, Vera
BookMark eNpNkV9PHCEUxUljE6365geYpK-u5c8wMI9qVqvRmFR9JhfmYtnswhQwsd--rNsY4YGbw-GXE843shdTREJOGD0TYqQ_YJ6ZYCOjQy--kANO1bAQPVN7n-Z9clzKirY1MqEZPSBPtynE2i3fagZXQ4pd8t0y1lADlg7i1P3CNWwvSncBBaeuWZbxN0TX5scZ4rvpGip29-iaHsrmiHz1sC54_P88JM9Xy6fLn4u7h-uby_O7hRODqAuNwnKruKfeczZxK3vurBKS4mC5tFwzIbiTjlJvFUWQ1INW1g4jQ2RSHJKbHXdKsDJzDhvIf02CYN6FlF8M5BrcGg02hhKjnfqJ9m502k5couqxUUEq3Vjfd6w5pz-vWKpZpdccW3zDtRr6gWnGmuts53qBBg3Rp-2_tT3hJrhWiA9NP1eKacplv414unvgciolo_-IyajZ9mY-9yb-AVRbirA
Cites_doi 10.18653/v1/P16-1105
10.18653/v1/2021.acl-long.277
10.18653/v1/2020.coling-main.138
10.18653/v1/D19-1035
10.18653/v1/P16-1072
10.18653/v1/P16-1123
10.3115/1690219.1690287
10.18653/v1/2021.emnlp-main.17
10.18653/v1/2020.acl-main.519
10.18653/v1/2020.acl-main.136
10.18653/v1/D17-1018
10.18653/v1/2022.acl-long.63
10.1016/j.eswa.2018.07.032
10.3115/v1/P14-1038
10.3115/1596374.1596399
10.1007/978-3-642-15939-8_10
10.18653/v1/P18-1047
10.18653/v1/2021.acl-long.486
10.18653/v1/2021.naacl-main.5
10.1007/s00521-021-05815-z
10.18653/v1/P16-1200
ContentType Journal Article
Copyright COPYRIGHT 2023 MDPI AG
2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: COPYRIGHT 2023 MDPI AG
– notice: 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID AAYXX
CITATION
ABUWG
AFKRA
AZQEC
BENPR
CCPQU
DWQXO
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
DOA
DOI 10.3390/app131910643
DatabaseName CrossRef
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest Central - New (Subscription)
ProQuest One Community College
ProQuest Central Korea
ProQuest Central Premium
ProQuest One Academic (New)
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest Central China
ProQuest Central
ProQuest One Academic UKI Edition
ProQuest Central Korea
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
DatabaseTitleList Publicly Available Content Database


CrossRef
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: BENPR
  name: ProQuest Central
  url: http://www.proquest.com/pqcentral?accountid=15518
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Sciences (General)
EISSN 2076-3417
ExternalDocumentID oai_doaj_org_article_e00f739bd4d04c9c8bd25e74eea5a578
A771802545
10_3390_app131910643
GroupedDBID .4S
2XV
5VS
7XC
8CJ
8FE
8FG
8FH
AADQD
AAFWJ
AAYXX
ADBBV
ADMLS
AFKRA
AFPKN
AFZYC
ALMA_UNASSIGNED_HOLDINGS
APEBS
ARCSS
BCNDV
BENPR
CCPQU
CITATION
CZ9
D1I
D1J
D1K
GROUPED_DOAJ
IAO
IGS
ITC
K6-
K6V
KC.
KQ8
L6V
LK5
LK8
M7R
MODMG
M~E
OK1
P62
PHGZM
PHGZT
PIMPY
PROAC
TUS
PMFND
ABUWG
AZQEC
DWQXO
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
PUEGO
ID FETCH-LOGICAL-c363t-8e3b2b72f0ff21d2b542cb7350e6b25b281332c5c00fb70ea50fa87bb691ee153
IEDL.DBID DOA
ISSN 2076-3417
IngestDate Wed Aug 27 01:30:34 EDT 2025
Sun Jun 29 15:50:35 EDT 2025
Tue Jun 10 21:20:04 EDT 2025
Tue Jul 01 04:34:17 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 19
Language English
License https://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c363t-8e3b2b72f0ff21d2b542cb7350e6b25b281332c5c00fb70ea50fa87bb691ee153
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-3158-9650
0000-0003-4904-7857
OpenAccessLink https://doaj.org/article/e00f739bd4d04c9c8bd25e74eea5a578
PQID 2876461811
PQPubID 2032433
ParticipantIDs doaj_primary_oai_doaj_org_article_e00f739bd4d04c9c8bd25e74eea5a578
proquest_journals_2876461811
gale_infotracacademiconefile_A771802545
crossref_primary_10_3390_app131910643
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2023-10-01
PublicationDateYYYYMMDD 2023-10-01
PublicationDate_xml – month: 10
  year: 2023
  text: 2023-10-01
  day: 01
PublicationDecade 2020
PublicationPlace Basel
PublicationPlace_xml – name: Basel
PublicationTitle Applied sciences
PublicationYear 2023
Publisher MDPI AG
Publisher_xml – name: MDPI AG
References Qiao (ref_6) 2022; 34
ref_14
ref_36
ref_13
ref_35
ref_12
ref_34
ref_11
ref_33
ref_10
ref_32
ref_31
ref_30
ref_19
E (ref_2) 2019; 30
ref_18
ref_17
ref_16
ref_38
ref_15
ref_37
Sutskever (ref_21) 2014; 27
ref_25
ref_24
ref_23
ref_22
ref_20
Bekoulis (ref_5) 2018; 114
ref_3
ref_29
ref_28
Zelenko (ref_1) 2003; 3
ref_27
ref_26
ref_9
ref_8
ref_4
ref_7
References_xml – ident: ref_28
– ident: ref_19
  doi: 10.18653/v1/P16-1105
– ident: ref_9
– ident: ref_25
  doi: 10.18653/v1/2021.acl-long.277
– ident: ref_29
  doi: 10.18653/v1/2020.coling-main.138
– ident: ref_30
– ident: ref_32
– ident: ref_37
  doi: 10.18653/v1/D19-1035
– ident: ref_18
  doi: 10.18653/v1/P16-1072
– ident: ref_34
– volume: 3
  start-page: 1082
  year: 2003
  ident: ref_1
  article-title: Kernel Methods for Relation Extraction
  publication-title: J. Mach. Learn. Res.
– ident: ref_17
  doi: 10.18653/v1/P16-1123
– ident: ref_23
  doi: 10.3115/1690219.1690287
– ident: ref_27
  doi: 10.18653/v1/2021.emnlp-main.17
– ident: ref_14
  doi: 10.18653/v1/2020.acl-main.519
– ident: ref_16
– ident: ref_7
  doi: 10.18653/v1/2020.acl-main.136
– ident: ref_11
  doi: 10.18653/v1/D17-1018
– ident: ref_12
  doi: 10.18653/v1/2022.acl-long.63
– volume: 114
  start-page: 34
  year: 2018
  ident: ref_5
  article-title: Joint entity recognition and relation extraction as a multi-head selection problem
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2018.07.032
– ident: ref_4
  doi: 10.3115/v1/P14-1038
– ident: ref_8
– ident: ref_31
– ident: ref_3
  doi: 10.3115/1596374.1596399
– ident: ref_33
  doi: 10.1007/978-3-642-15939-8_10
– ident: ref_10
– volume: 27
  start-page: 1227
  year: 2014
  ident: ref_21
  article-title: Sequence to sequence learning with neural networks
  publication-title: Adv. Neural Inf. Process. Syst.
– ident: ref_35
  doi: 10.18653/v1/P18-1047
– ident: ref_13
– ident: ref_26
  doi: 10.18653/v1/2021.acl-long.486
– ident: ref_38
– ident: ref_15
  doi: 10.18653/v1/2021.naacl-main.5
– ident: ref_36
– ident: ref_22
– ident: ref_20
– volume: 34
  start-page: 3471
  year: 2022
  ident: ref_6
  article-title: A joint model for entity and relation extraction based on bert
  publication-title: Neural Comput. Appl.
  doi: 10.1007/s00521-021-05815-z
– ident: ref_24
  doi: 10.18653/v1/P16-1200
– volume: 30
  start-page: 1793
  year: 2019
  ident: ref_2
  article-title: Survey of entity relationship extraction based on deep learning
  publication-title: J. Softw.
SSID ssj0000913810
Score 2.2654662
Snippet Although entity and relation joint extraction can obtain relational triples efficiently and accurately, there are a number of problems; for instance, the...
SourceID doaj
proquest
gale
crossref
SourceType Open Website
Aggregation Database
Index Database
StartPage 10643
SubjectTerms Analysis
Computational linguistics
Deep learning
Efficiency
gate unit
Innovations
joint extraction
Language processing
Methods
Natural language interfaces
nested entities
Neural networks
relation overlap
Semantics
span
SummonAdditionalLinks – databaseName: ProQuest Technology Collection
  dbid: 8FG
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV07bxQxELYgNFAgEkAcBOQCBBQr_Fx7K5SgO6JIoSGR0lkePyBFdsPdIvHz8ez6jlBAu-tiNJ63Z74h5HUIreFZ6EYKrxqVW9tYm1TTxU54zyFIj4ni2Zf25EKdXurLWnDb1LbKrU2cDHUcAtbIP5TIvlVt8Uf8482PBrdG4etqXaFxl9zjokgSToqvPu9qLIh5aTmb-91lye7xVZgXoePoiP_yRBNg_7_M8uRrVo_Iwxok0qP5VvfJndQfkAe3oAMPyH5Vyg19V5Gj3z8m56fDVT_S5a9xPc8r0CHTZUVNpb6PdNf7Ro-L-4q0HFn236cuAPq1GIbpEFbU6FnCmeCrzfUTcrFann86aerahCbIVo6NTRIEGJFZzoJHAVqJAEZqlloQGoQteakIOjCWwbDkNcveGoC24ykVC_iU7PVDn54RKoXOIhsQsvMKInS2MwykZ8AT80kvyJstC93NjI7hSlaBrHa3Wb0gx8jf3RnEtJ4-DOtvrqqIS4UeIzuIKjIVumAhCp2MSoVCXwzLgrzF23GoechGXwcICqmIYeWOjEE4uxISLsjh9gJdVcmN-yNAz___-wW5jzvl5469Q7I3rn-mlyXyGOHVJF6_AXgn1vg
  priority: 102
  providerName: ProQuest
Title Joint Extraction of Entities and Relations Based on Enhanced Span and Gate Mechanism
URI https://www.proquest.com/docview/2876461811
https://doaj.org/article/e00f739bd4d04c9c8bd25e74eea5a578
Volume 13
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAFT
  databaseName: Open Access Digital Library
  customDbUrl:
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: KQ8
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html
  providerName: Colorado Alliance of Research Libraries
– providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: DOA
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVEBS
  databaseName: Inspec with Full Text
  customDbUrl:
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: ADMLS
  dateStart: 20120901
  isFulltext: true
  titleUrlDefault: https://www.ebsco.com/products/research-databases/inspec-full-text
  providerName: EBSCOhost
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: M~E
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl: http://www.proquest.com/pqcentral?accountid=15518
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: BENPR
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Technology Collection
  customDbUrl:
  eissn: 2076-3417
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0000913810
  issn: 2076-3417
  databaseCode: 8FG
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/technologycollection1
  providerName: ProQuest
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwEB5BucAB0QJioax8AAGHCMeP2D52UZaqUisErdSb5XFs0UOzqBskfj7jJK2WA-LCNfJh9M07nvkM8CbGxtRZ6EqKoCqVG1tZm1TlOidCqDHKUBrF07Pm-EKdXOrLnae-ykzYRA88AfcxcZ6NdNipjqvoosVO6GRUSkEHMrcSfSmN7TRTYwx2daGumibdJfX15T64JnOrSwr-IweNVP1_C8hjllk_gcdzeciOJrH24V7qD-DRDmngAezP7rhl72fO6A9P4fxkc9UPrP013EybCmyTWTvzpbLQd-xu6o2tKHF1jI60_ffx_p99o5AwHir_0thpKtvAV9vrZ3Cxbs8_HVfzgwlVlI0cKpskCjQi85xF3QnUSkQ0UvPUoNAoLHWkIupImKLhhCDPwRrExtUpUex7Dnv9pk8vgEmhs8gGhXRBYYfOOsNRBo514iHpBby9hdD_mHgxPPUTBWq_C_UCVgXfuzOFzXr8QDr2s479v3S8gHdFO774XIExzKsDJGphr_JHxhQiOyoGF3B4q0A_O-PWU1PYqIZKmfrl_5DmFTwsb85PE32HsDfc_EyvqTIZcAn37frzEh6s2rMvX5ejSf4GMzHi3Q
linkProvider Directory of Open Access Journals
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV07bxQxELaiUAAFIgHEQQguiIBihZ9rb4GiBO64PC4NFymdsb12SMFuuFsE_Kn8xnj2cYQCurS7Lkbj8Tcz9sw3CL3yPlc0MplxZkUmYq4zrYPIirJg1lLnuYVEcXaST0_F4Zk8W0NXQy8MlFUOmNgCdVl7uCN_lyL7XOTJH9Hdy-8ZTI2C19VhhEZnFkfh98-Usi3fH3xM-7vD2GQ8_zDN-qkCmec5bzIduGNOsUhiZLRkTgrmneKShNwx6ZhOaRvz0hMSnSLBShKtVs7lBQ2BwpSIBPl3BOccuPr15NPqTgc4NjUlXX095wWBV2iajJyC4__L87UDAv7lBlrfNnmIHvRBKd7rrGgDrYVqE92_QVW4iTZ6EFjiNz1T9dtHaH5YX1QNHv9qFl1_BK4jHvcsrdhWJV7V2uH95C5LnJaMq69t1QH-nICoXQQ3eHgWoAf5YvntMTq9FYU-QetVXYWnCHMmI4vKMV5Y4UpX6EIRxy1xNBAb5AjtDCo0lx0bh0lZDKja3FT1CO2DfldrgEO7_VAvzk1_JE1I8iheuFKURPjCa1cyGZQISUKbgGyEXsPuGDjpoEbbNywkUYEzy-wpBfR5KQQdoa1hA00PAUvzx2Cf_f_3S3R3Op8dm-ODk6Pn6B7Ms--qBbfQerP4EV6kqKdx262pYfTltm37GkRIE8k
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELaqrYTggGgBsVDAByrgENXPODlUqEuz6oOuKmil3oKf0ANJ2Q0C_iK_Ck_iXcoBbr0mPlgz43nYM9-H0Atrc0UDkxlnWmQi5EVWFF5kpSuZ1tRYrqFQPJnlB-fi6EJerKFfy1kYaKtc-sTeUbvWwh35Tszsc5HHeER3QmqLON2fvrn6mgGDFLy0Luk0dKJZcLs93Fga8jj2P7_Hcm6xe7gfdb_N2LQ6e3uQJcaBzPKcd1nhuWFGsUBCYNQxIwWzRnFJfG6YNKyIJR2z0hISjCJeSxJ0oYzJS-o9BQaJGA7WFcyLjtD6pJqdvl_d-AACZ0HJ0H3PeUngjZrGI0AhLfgrLvb0Af8KEn3km95Dd1PKivcGG9tAa77ZRHeuARluoo3kIhb4VcKxfn0fnR21l02Hqx_dfJiewG3AVcJwxbpxeNWJhycxmDocl1TN574nAX-IbqpfBPd7-MTDhPLl4ssDdH4jIn2IRk3b-EcIcyYDC8owXmphnCmLUhHDNTHUE-3lGG0vRVhfDVgddaxxQNT1dVGP0QTku1oDCNv9h3b-qU4HtvZxP1GPxglHhC1tYRyTXgkfd6ijmxujl6CdGvwAiFGncYa4VUDUqveUAnC9mKCO0dZSgXVyEIv6jzk__v_v5-hWtPP63eHs-Am6DWT3QyvhFhp182_-aUyJOvMs2RpGH2_avH8Dw4Ieow
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=Joint+Extraction+of+Entities+and+Relations+Based+on+Enhanced+Span+and+Gate+Mechanism&rft.jtitle=Applied+sciences&rft.au=Nan+Zhang&rft.au=Junfang+Xin&rft.au=Qiang+Cai&rft.au=Vera+Chung&rft.date=2023-10-01&rft.pub=MDPI+AG&rft.eissn=2076-3417&rft.volume=13&rft.issue=19&rft.spage=10643&rft_id=info:doi/10.3390%2Fapp131910643&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_e00f739bd4d04c9c8bd25e74eea5a578
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2076-3417&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2076-3417&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2076-3417&client=summon