MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank
Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manua...
Gespeichert in:
| Veröffentlicht in: | Journal of biomedical semantics Jg. 8; H. 1; S. 15 - 9 |
|---|---|
| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
London
BioMed Central
17.04.2017
Springer Nature B.V BMC |
| Schlagworte: | |
| ISSN: | 2041-1480, 2041-1480 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Background
MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized.
Methods
We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module.
Results
We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F
1
-score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale.
Conclusions
We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. Availability:
http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/
. |
|---|---|
| AbstractList | Abstract Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized. Methods We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module. Results We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F1-score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale. Conclusions We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. Availability: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ . Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized. Methods We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module. Results We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F 1 -score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale. Conclusions We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. Availability: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ . Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized. Methods We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module. Results We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F1-score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale. Conclusions We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. Availability: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/. MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized. We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module. We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F -score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale. We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ . MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized.BACKGROUNDMeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized.We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module.METHODSWe propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module.We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F1-score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale.RESULTSWe assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F1-score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale.We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame.CONCLUSIONSWe conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame.http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ .AVAILABILITYhttp://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ . |
| ArticleNumber | 15 |
| Author | Mao, Yuqing Lu, Zhiyong |
| Author_xml | – sequence: 1 givenname: Yuqing surname: Mao fullname: Mao, Yuqing organization: Nanjing University of Chinese Medicine, National Center for Biotechnology Information (NCBI) – sequence: 2 givenname: Zhiyong surname: Lu fullname: Lu, Zhiyong email: zhiyong.lu@nih.gov organization: National Center for Biotechnology Information (NCBI) |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28412964$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9Uk1v1DAQtVARLaU_gAuKxIVLwPY4icMBCVWUVmoBqdytcTJZvGTtYicF_j1Ot1TbSmDJsjXz3pvPp2zPB0-MPRf8tRC6fpMEgKxLLpp8JZTwiB1IrkQplOZ7O_99dpTSmucDILiGJ2xfaiVkW6sDdnJBl6fFp_DzbYHzFDY4ua64sTnf0y_nVwVOxZfZXlBfpA5HKq4dFiNh9ItzCkVE__0ZezzgmOjo9j1klycfvh6fluefP54dvz8vu5rLqRwUSdvUpAdorKh7ZRGgaoQm3ZHSVaU1WkA5qI4r6GVtoSfeZK8E1cIhO9uq9gHX5iq6DcbfJqAzN4YQVwZjLmAk0wshWmvRDqJWakBNpHrQ9SBbXUG1aL3bal3NdkN9R36KON4Tve_x7ptZhWtTQZtbp7PAq1uBGH7MlCazcamjcURPYU5GaK3bqmnkEuvlA-g6zNHnRmVUq6pKAfCMerGb0V0qf4eVAWIL6GJIKdJwBxHcLDthtjth8k6YZScMZE7zgNO5KQ85LEW58b9MuWWmHMWvKO4k_U_SH3qOx9w |
| CitedBy_id | crossref_primary_10_2196_15922 crossref_primary_10_2478_cait_2020_0043 crossref_primary_10_1093_bib_bbac083 crossref_primary_10_1016_j_jbi_2022_104235 crossref_primary_10_1186_s12874_021_01337_3 crossref_primary_10_1097_MD_0000000000031441 crossref_primary_10_1186_s12874_019_0819_4 crossref_primary_10_3103_S0005105520060023 crossref_primary_10_3389_fpubh_2019_00188 crossref_primary_10_1007_s42399_025_02046_4 crossref_primary_10_1177_01655515231161557 crossref_primary_10_1186_s12859_021_04044_4 crossref_primary_10_1007_s10115_023_01862_1 crossref_primary_10_1016_j_heliyon_2023_e23781 crossref_primary_10_1007_s00521_021_06053_z crossref_primary_10_1038_s41523_025_00809_9 crossref_primary_10_4103_IJO_IJO_718_23 crossref_primary_10_1016_j_joi_2025_101648 crossref_primary_10_1186_s12859_022_04803_x crossref_primary_10_3390_jpm14050545 crossref_primary_10_1109_TCBB_2020_3016355 crossref_primary_10_1371_journal_pntd_0006602 crossref_primary_10_1016_j_plasmid_2024_102731 crossref_primary_10_1016_j_asoc_2019_03_041 crossref_primary_10_3389_fninf_2023_1215261 crossref_primary_10_1016_j_jbi_2021_103699 crossref_primary_10_1016_j_jbi_2022_104106 crossref_primary_10_1093_bib_bbaa057 crossref_primary_10_1007_s10502_024_09469_3 crossref_primary_10_1093_bib_bbaa394 crossref_primary_10_1146_annurev_biodatasci_080917_013459 crossref_primary_10_1371_journal_pone_0256248 crossref_primary_10_1097_MD_0000000000038873 crossref_primary_10_1371_journal_pbio_2005343 crossref_primary_10_1371_journal_pone_0270196 crossref_primary_10_1007_s11192_022_04292_y crossref_primary_10_1093_jamia_ocz085 crossref_primary_10_1186_s12859_018_2534_2 crossref_primary_10_3389_fonc_2020_606400 crossref_primary_10_3390_healthcare13080927 crossref_primary_10_1016_j_artmed_2021_102053 crossref_primary_10_3390_math10162867 |
| Cites_doi | 10.1109/IJCNN.2010.5596486 10.3233/ISB-00343 10.1093/database/bau074 10.1093/bioinformatics/btv237 10.1186/1471-2105-15-179 10.1016/j.jbi.2014.08.004 10.1197/jamia.M2431 10.1007/s10791-006-9019-z 10.1093/bib/bbl035 10.1145/1552303.1552304 10.1186/1471-2105-12-223 10.1016/j.datak.2014.09.002 10.1093/bioinformatics/bti783 10.1093/database/bap018 10.1097/00001888-200510000-00014 10.1214/aoms/1177703732 10.1214/aos/1013203451 10.1073/pnas.0307509100 10.1186/1747-5333-3-2 10.1145/312624.312681 10.1016/j.jbi.2008.12.007 10.5626/JCSE.2012.6.2.151 10.1186/1471-2105-9-S5-S3 10.1007/s10791-008-9074-8 10.1093/bioinformatics/btp338 10.1007/s10791-009-9112-1 10.1093/bioinformatics/btw294 10.1561/1500000016 10.1186/1472-6947-9-7 10.1145/1102351.1102363 10.1093/database/bau086 10.1093/bioinformatics/btp249 10.1186/gm376 10.6028/NIST.SP.500-225.city 10.1371/journal.pone.0115681 10.1145/1273496.1273513 10.1016/j.jbi.2012.05.005 10.1145/1277741.1277809 10.1093/bioinformatics/btr223 10.1186/1471-2105-11-166 10.1145/1526709.1526738 10.1002/asi.23063 10.1186/s12859-015-0564-6 10.1186/1471-2105-9-S11-S11 10.1136/amiajnl-2010-000055 10.1023/A:1012782908347 10.1093/bioinformatics/bts156 10.1142/9789812772435_0026 10.1016/j.jbi.2010.11.001 10.1093/bioinformatics/17.4.319 10.1186/1471-2105-8-423 |
| ContentType | Journal Article |
| Copyright | The Author(s). 2017 Copyright BioMed Central 2017 |
| Copyright_xml | – notice: The Author(s). 2017 – notice: Copyright BioMed Central 2017 |
| DBID | C6C AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7X7 7XB 88E 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AFKRA AZQEC BBNVY BENPR BGLVJ BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. L6V LK8 M0S M1P M7P M7S PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS 7X8 5PM DOA |
| DOI | 10.1186/s13326-017-0123-3 |
| DatabaseName | Springer Nature OA Free Journals CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Materials Science & Engineering ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials Biological Science Collection ProQuest Central Technology collection Natural Science Collection ProQuest One Community College ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Engineering Collection Biological Sciences Health & Medical Collection (Alumni Edition) PML(ProQuest Medical Library) Biological Science Database Engineering Database ProQuest Central Premium ProQuest One Academic Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection ProQuest Engineering Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Engineering Database ProQuest Biological Science Collection ProQuest One Academic Eastern Edition ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition Materials Science & Engineering Collection ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | Publicly Available Content Database MEDLINE MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Languages & Literatures Mathematics |
| EISSN | 2041-1480 |
| EndPage | 9 |
| ExternalDocumentID | oai_doaj_org_article_d1119bbabf1644fa8ee4d386f2985359 PMC5392968 28412964 10_1186_s13326_017_0123_3 |
| Genre | Journal Article |
| GroupedDBID | 0R~ 53G 5VS 7X7 88E 8FE 8FG 8FH 8FI 8FJ AAFWJ AAJSJ AASML ABDBF ABJCF ABUWG ACGFO ACGFS ACIWK ACPRK ACUHS ADBBV ADRAZ ADUKV AEGXH AENEX AFKRA AFPKN AHBYD AHSBF AHYZX AIAGR ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BBNVY BCNDV BENPR BFQNJ BGLVJ BHPHI BMC BPHCQ BVXVI C6C CCPQU DIK E3Z EBD EBLON EBS EJD ESX F5P FYUFA GROUPED_DOAJ GX1 H13 HCIFZ HMCUK HYE IAO IEA IHR INH INR ITC KQ8 L6V LK8 M1P M48 M7P M7S ML~ M~E O5R O5S OK1 PGMZT PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PTHSS PUEGO RBZ RNS ROL RPM RSV SMT SOJ TUS UKHRP AAYXX AFFHD CITATION ALIPV CGR CUY CVF ECM EIF NPM 3V. 7XB 8FK AZQEC DWQXO GNUQQ K9. PKEHL PQEST PQUKI PRINS 7X8 5PM |
| ID | FETCH-LOGICAL-c602t-f4e2b76e8f37b16d4ba335718e8ce485588ab3a2f4c043d26b3de07e8c23493 |
| IEDL.DBID | RSV |
| ISICitedReferencesCount | 59 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000399186200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2041-1480 |
| IngestDate | Tue Oct 14 17:31:31 EDT 2025 Tue Nov 04 01:59:04 EST 2025 Sun Nov 09 09:03:11 EST 2025 Sun Oct 19 00:04:42 EDT 2025 Mon Jul 21 05:45:07 EDT 2025 Tue Nov 18 19:42:09 EST 2025 Sat Nov 29 07:46:25 EST 2025 Sat Sep 06 07:20:56 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | Target Article Inductive Logic Programming Unify Medical Language System Text Classification MeSH Term |
| Language | English |
| License | Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c602t-f4e2b76e8f37b16d4ba335718e8ce485588ab3a2f4c043d26b3de07e8c23493 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://link.springer.com/10.1186/s13326-017-0123-3 |
| PMID | 28412964 |
| PQID | 1894554330 |
| PQPubID | 2040220 |
| PageCount | 9 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_d1119bbabf1644fa8ee4d386f2985359 pubmedcentral_primary_oai_pubmedcentral_nih_gov_5392968 proquest_miscellaneous_1888957729 proquest_journals_1894554330 pubmed_primary_28412964 crossref_primary_10_1186_s13326_017_0123_3 crossref_citationtrail_10_1186_s13326_017_0123_3 springer_journals_10_1186_s13326_017_0123_3 |
| PublicationCentury | 2000 |
| PublicationDate | 2017-04-17 |
| PublicationDateYYYYMMDD | 2017-04-17 |
| PublicationDate_xml | – month: 04 year: 2017 text: 2017-04-17 day: 17 |
| PublicationDecade | 2010 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London – name: England |
| PublicationTitle | Journal of biomedical semantics |
| PublicationTitleAbbrev | J Biomed Semant |
| PublicationTitleAlternate | J Biomed Semantics |
| PublicationYear | 2017 |
| Publisher | BioMed Central Springer Nature B.V BMC |
| Publisher_xml | – name: BioMed Central – name: Springer Nature B.V – name: BMC |
| References | Y Mao (123_CR28) 2014; 2014 Q Wu (123_CR67) 2010; 13 123_CR71 123_CR70 123_CR31 BL Humphreys (123_CR72) 1993; 81 123_CR32 JG Mork (123_CR49) 2013 A Névéol (123_CR52) 2009; 42 MR Tennant (123_CR18) 2002; 90 123_CR30 123_CR34 K Liu (123_CR47) 2014; 129816 K Auken Van (123_CR29) 2014; 2014 AJ Jimeno-Yepes (123_CR11) 2011; 12 123_CR26 D Trieschnigg (123_CR41) 2009; 25 S Peng (123_CR74) 2016; 32 SD Jani (123_CR19) 2010; 11 A Névéol (123_CR1) 2011; 44 NR Smalheiser (123_CR6) 2008; 3 LD Gruppen (123_CR17) 2005; 80 S Sohn (123_CR37) 2008; 15 123_CR60 T-Y Liu (123_CR43) 2009; 3 123_CR61 123_CR64 123_CR62 123_CR66 AR Aronson (123_CR51) 2004; 11 JL D’Souza (123_CR14) 2014; 9 G Tsatsaronis (123_CR46) 2015; 16 S Bhattacharya (123_CR9) 2011; 27 Z Lu (123_CR27) 2012; 2012 S Zhu (123_CR10) 2009; 25 I Partalas (123_CR54) 2013 MA Sartor (123_CR22) 2012; 28 W Liu (123_CR8) 2014; 65 T Ono (123_CR24) 2014; 15 T Nakazato (123_CR25) 2008; 8 A Mottaz (123_CR21) 2008; 9 123_CR5 DR Masys (123_CR20) 2001; 17 123_CR57 R Islamaj Dogan (123_CR2) 2009; 2009 Y Mao (123_CR44) 2014 123_CR58 PJ Huber (123_CR59) 1964; 35 VI Torvik (123_CR7) 2009; 3 D Metzler (123_CR65) 2007; 10 ME Ruiz (123_CR33) 2002; 5 C Quoc (123_CR68) 2007 123_CR48 G Tsoumakas (123_CR35) 2013 Z Lu (123_CR4) 2009; 12 SC Burrows (123_CR16) 1999; 87 A Névéol (123_CR36) 2008; 9 JP DeShazo (123_CR13) 2009; 9 K Liu (123_CR73) 2015; 31 WA Cheung (123_CR23) 2012; 4 ME Funk (123_CR55) 1983; 71 123_CR42 J Lin (123_CR56) 2007; 8 A Jimeno-Yepes (123_CR39) 2012; 6 123_CR40 JG Mork (123_CR53) 2014 WJWK Wilbur (123_CR38) 2014 123_CR45 JH Friedman (123_CR63) 2001; 29 M Huang (123_CR3) 2011; 18 C Perez-Iratxeta (123_CR12) 2007; 8 KW Boyack (123_CR15) 2004; 101 PF Brown (123_CR69) 1993; 19 P Ruch (123_CR50) 2006; 22 |
| References_xml | – volume: 81 start-page: 170 issue: 2 year: 1993 ident: 123_CR72 publication-title: Bull Med Libr Assoc – ident: 123_CR58 doi: 10.1109/IJCNN.2010.5596486 – volume: 8 start-page: 53 issue: 1 year: 2008 ident: 123_CR25 publication-title: In Silico Biol doi: 10.3233/ISB-00343 – volume: 2014 start-page: bau074 year: 2014 ident: 123_CR29 publication-title: Database doi: 10.1093/database/bau074 – volume: 31 start-page: 339 issue: 12 year: 2015 ident: 123_CR73 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btv237 – volume: 15 start-page: 179 issue: 1 year: 2014 ident: 123_CR24 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-15-179 – ident: 123_CR26 doi: 10.1016/j.jbi.2014.08.004 – volume: 15 start-page: 546 issue: 4 year: 2008 ident: 123_CR37 publication-title: J Am Med Inform Assoc doi: 10.1197/jamia.M2431 – volume: 10 start-page: 257 issue: 3 year: 2007 ident: 123_CR65 publication-title: Inf Retr doi: 10.1007/s10791-006-9019-z – volume: 87 start-page: 471 issue: 4 year: 1999 ident: 123_CR16 publication-title: Bull Med Libr Assoc – volume: 8 start-page: 88 issue: 2 year: 2007 ident: 123_CR12 publication-title: Brief Bioinform doi: 10.1093/bib/bbl035 – volume: 3 start-page: 11 issue: 3 year: 2009 ident: 123_CR7 publication-title: ACM Trans Knowl Discov Data doi: 10.1145/1552303.1552304 – ident: 123_CR34 – volume: 12 start-page: 223 issue: 1 year: 2011 ident: 123_CR11 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-12-223 – ident: 123_CR48 doi: 10.1016/j.datak.2014.09.002 – volume-title: Proceedings of Question Answering Lab at CLEF year: 2014 ident: 123_CR44 – volume: 22 start-page: 658 issue: 6 year: 2006 ident: 123_CR50 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti783 – volume: 2009 start-page: bap018 year: 2009 ident: 123_CR2 publication-title: Database doi: 10.1093/database/bap018 – volume: 80 start-page: 940 issue: 10 year: 2005 ident: 123_CR17 publication-title: Acad Med doi: 10.1097/00001888-200510000-00014 – volume: 35 start-page: 73 issue: 1 year: 1964 ident: 123_CR59 publication-title: Ann Math Stat doi: 10.1214/aoms/1177703732 – ident: 123_CR40 – volume: 29 start-page: 1189 year: 2001 ident: 123_CR63 publication-title: Ann Stat. doi: 10.1214/aos/1013203451 – volume: 2012 start-page: bas043 year: 2012 ident: 123_CR27 publication-title: Database – volume: 101 start-page: 5192 issue: suppl 1 year: 2004 ident: 123_CR15 publication-title: Proc Natl Acad Sci doi: 10.1073/pnas.0307509100 – volume: 3 start-page: 2 issue: 1 year: 2008 ident: 123_CR6 publication-title: J Biomed Discov Collab doi: 10.1186/1747-5333-3-2 – ident: 123_CR61 – volume: 90 start-page: 181 issue: 2 year: 2002 ident: 123_CR18 publication-title: J Med Libr Assoc – ident: 123_CR71 doi: 10.1145/312624.312681 – ident: 123_CR5 – volume: 42 start-page: 814 issue: 5 year: 2009 ident: 123_CR52 publication-title: J Biomed Inform doi: 10.1016/j.jbi.2008.12.007 – volume: 6 start-page: 151 issue: 2 year: 2012 ident: 123_CR39 publication-title: JCSE doi: 10.5626/JCSE.2012.6.2.151 – volume: 9 start-page: S3 issue: Suppl 5 year: 2008 ident: 123_CR21 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-S5-S3 – volume: 11 start-page: 268 issue: Pt 1 year: 2004 ident: 123_CR51 publication-title: Medinfo – volume: 12 start-page: 69 issue: 1 year: 2009 ident: 123_CR4 publication-title: Inf Retr doi: 10.1007/s10791-008-9074-8 – volume: 25 start-page: 1944 issue: 15 year: 2009 ident: 123_CR10 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btp338 – volume: 13 start-page: 254 issue: 3 year: 2010 ident: 123_CR67 publication-title: Inf Retr doi: 10.1007/s10791-009-9112-1 – volume: 129816 start-page: 100 year: 2014 ident: 123_CR47 publication-title: Risk – volume: 32 start-page: 70 issue: 12 year: 2016 ident: 123_CR74 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw294 – start-page: 1328 volume-title: Working Notes for CLEF 2014 Conference, Sheffield, UK year: 2014 ident: 123_CR53 – volume: 3 start-page: 225 issue: 3 year: 2009 ident: 123_CR43 publication-title: Found Trends Inf Retr doi: 10.1561/1500000016 – volume: 9 start-page: 7 issue: 1 year: 2009 ident: 123_CR13 publication-title: BMC Med Inform Decis Mak doi: 10.1186/1472-6947-9-7 – volume: 71 start-page: 176 issue: 2 year: 1983 ident: 123_CR55 publication-title: Bull Med Libr Assoc – volume-title: BioASQ@ CLEF year: 2013 ident: 123_CR35 – ident: 123_CR64 doi: 10.1145/1102351.1102363 – ident: 123_CR45 – volume: 2014 start-page: bau086 year: 2014 ident: 123_CR28 publication-title: Database doi: 10.1093/database/bau086 – volume: 25 start-page: 1412 issue: 11 year: 2009 ident: 123_CR41 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btp249 – volume: 4 start-page: 75 issue: 9 year: 2012 ident: 123_CR23 publication-title: Genome Med doi: 10.1186/gm376 – ident: 123_CR70 doi: 10.6028/NIST.SP.500-225.city – volume: 9 start-page: e115681 year: 2014 ident: 123_CR14 publication-title: PLoS One doi: 10.1371/journal.pone.0115681 – ident: 123_CR62 doi: 10.1145/1273496.1273513 – ident: 123_CR31 – ident: 123_CR60 doi: 10.1016/j.jbi.2012.05.005 – ident: 123_CR66 doi: 10.1145/1277741.1277809 – volume: 27 start-page: i120 issue: 13 year: 2011 ident: 123_CR9 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btr223 – volume: 11 start-page: 166 issue: 1 year: 2010 ident: 123_CR19 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-166 – ident: 123_CR57 doi: 10.1145/1526709.1526738 – volume: 65 start-page: 765 issue: 4 year: 2014 ident: 123_CR8 publication-title: J Assoc Inf Sci Technol doi: 10.1002/asi.23063 – volume: 16 start-page: 138 issue: 1 year: 2015 ident: 123_CR46 publication-title: BMC Bioinformatics doi: 10.1186/s12859-015-0564-6 – volume: 9 start-page: S11 issue: Suppl 11 year: 2008 ident: 123_CR36 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-S11-S11 – start-page: 1 volume-title: BioASQ@ CLEF year: 2013 ident: 123_CR54 – start-page: 193 volume-title: NIPS’07 year: 2007 ident: 123_CR68 – volume: 18 start-page: 660 issue: 5 year: 2011 ident: 123_CR3 publication-title: J Am Med Inform Assoc doi: 10.1136/amiajnl-2010-000055 – ident: 123_CR42 – volume-title: BioASQ@ CLEF year: 2013 ident: 123_CR49 – volume: 19 start-page: 263 issue: 2 year: 1993 ident: 123_CR69 publication-title: Comput Linguist – volume: 5 start-page: 87 issue: 1 year: 2002 ident: 123_CR33 publication-title: Inf Retr doi: 10.1023/A:1012782908347 – volume: 28 start-page: 1408 issue: 10 year: 2012 ident: 123_CR22 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts156 – ident: 123_CR30 doi: 10.1142/9789812772435_0026 – volume: 44 start-page: 310 issue: 2 year: 2011 ident: 123_CR1 publication-title: J Biomed Inform doi: 10.1016/j.jbi.2010.11.001 – volume-title: AMIA year: 2014 ident: 123_CR38 – volume: 17 start-page: 319 issue: 4 year: 2001 ident: 123_CR20 publication-title: Bioinformatics doi: 10.1093/bioinformatics/17.4.319 – ident: 123_CR32 – volume: 8 start-page: 423 issue: 1 year: 2007 ident: 123_CR56 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-8-423 |
| SSID | ssj0000331083 |
| Score | 2.376358 |
| Snippet | Background
MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly... MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important... Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly... Abstract Background MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task... |
| SourceID | doaj pubmedcentral proquest pubmed crossref springer |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 15 |
| SubjectTerms | Abstracting and Indexing - methods Algorithms Artificial intelligence Automation Benchmarking Bibliographic data bases Bioinformatics Citation analysis Classification Combinatorial Libraries Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computers Data Mining and Knowledge Discovery Documents Gene expression Indexing Inductive Logic Programming Information retrieval International conferences Language Learning Logic programming Machine Learning Mathematics Mathematics and Statistics Medical Subject Headings Medical Subject Headings-MeSH MeSH Term Neural networks Parameter estimation Post-processing PubMed Query expansion R&D Research & development Semantics Semantics-Enabled Biomedical Information Retrieval Subject heading schemes Target Article Text Classification Unify Medical Language System Word sense disambiguation |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Nb9QwEB2higMXxGcJFGQkxAEUNfE4jtMbIFY9bFeVilBvlh07sBJKUJMtf79jJxvt8nnhGjuK9TyTeZNx3gC8qgWWyguV1rK0qfDWpsYVTaowd5JMSPLYJeLzslyt1OVldb7T6iucCRvlgUfgjh05Y2WtsQ0Re9EY5b1wqGTDK4o0Rfx1j1jPTjIV38FItEXhVMbMlTzuKRnjIXkOJy05prgXiKJe_-9I5q9nJX8qmMY4tLgHdycCyd6NC78Pt3z7AA6X02fHnr1my1kpuX8IizN_ccpW3Y8TZjZDFwVaWbwWdRLpEcwM7Hxjz7xjPW2YZ9drw6ZmEl_Y0LHQ1v0RXCw-fvpwmk69Ewj0jA9pIzy3pfSqwdLm0glrEAsKRF7VPgjCKGUsGt6IOhPouLTofFbSKEdR4WM4aLvWPwFmVeGqoq4qWzvRYGgAaIsmN74kwkv5WgLZFkZdT7LiobvFNx3TCyX1iLwm5HVAXmMCb-Zbvo-aGn-b_D7szTwxyGHHC2QkejIS_S8jSeBou7N68tFe56oSRKYQswRezsPkXaFkYlrfbcIcpaoiZCAJHI6GMK-EAnseitYJlHsmsrfU_ZF2_TUqeBeBlUqVwNutMe0s609IPP0fSDyDOzz6gEjz8ggOhquNfw636-th3V-9iE50A7aTHQI priority: 102 providerName: Directory of Open Access Journals – databaseName: Engineering Database dbid: M7S link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB5B4cAFyqsNFGQkxAEUNbEdx-aCCmLVw3ZVaRHqzbJju12pSsomW_4-ttcbWB69cLUdaZxvxp7xjL4BeN1QUnNLed6wWufUap0rU7mck9Iwr0IMxy4RX6f1bMbPzsRpenDrU1nl5kyMB7XpmvBGflhyQf3V58PvD1ff8tA1KmRXUwuN23AnsCTgWLo3H99YCuKdF05SMrPk7LD3IRkOIXSot8QkJ1vXUWTt_5ur-WfF5G9p03gbTR787z524X7yQ9HRWnEewi3bPoK9aXq97NEbNB0Jl_vHMDmx82M0676_R2o1dJHnFcWxSLfoZURqQKcrfWIN6j3uFl0vFEo9Kc7R0KHQHf4JzCefv3w6zlMLBo9dgYfcUYt1zSx3pNYlM1QrQip_n1ne2MArw7nSRGFHm4ISg5kmxha1n8WECvIUdtqutfuANK-MqBohdGOoI6GPoK5cqWzt_WYf9mVQbHCQTWInD00yLmWMUjiTa-ikh04G6CTJ4O34ydWamuOmxR8DuOPCwKodB7rluUxGKo0_-IXWSjsfRFKnuLXUEM4cFt6rqUQGBxtMZTL1Xv4ENINX47Q30pB5Ua3tVmEN56IKgUwGe2tNGiXx_kEZct8Z1Fs6tiXq9ky7uIhE4FVwbhnP4N1GG38R619_4tnNm3gO93A0D5qX9QHsDMuVfQF3m-th0S9fRvv6AQWNKvI priority: 102 providerName: ProQuest |
| Title | MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank |
| URI | https://link.springer.com/article/10.1186/s13326-017-0123-3 https://www.ncbi.nlm.nih.gov/pubmed/28412964 https://www.proquest.com/docview/1894554330 https://www.proquest.com/docview/1888957729 https://pubmed.ncbi.nlm.nih.gov/PMC5392968 https://doaj.org/article/d1119bbabf1644fa8ee4d386f2985359 |
| Volume | 8 |
| WOSCitedRecordID | wos000399186200001&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: PRVADU databaseName: Open Access: BioMedCentral Open Access Titles customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: RBZ dateStart: 20100101 isFulltext: true titleUrlDefault: https://www.biomedcentral.com/search/ providerName: BioMedCentral – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: DOA dateStart: 20100101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: M~E dateStart: 20100101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: M7P dateStart: 20100101 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Engineering Database customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: M7S dateStart: 20100101 isFulltext: true titleUrlDefault: http://search.proquest.com providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: BENPR dateStart: 20100101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Health & Medical Collection customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: 7X7 dateStart: 20100101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: PIMPY dateStart: 20100101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 2041-1480 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000331083 issn: 2041-1480 databaseCode: RSV dateStart: 20101201 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/eLvHCXMwnV1Lb9QwEB7RlgMceBQogRIZCXEARU1sJ3a4UdRVkXZXURdVy8myY6eshBK0yZa_j-1NIhYKElxy8EMajWc8M57JNwCvSkoYN5RHZcZURI1SkdRpFXGS6MyKUIZ9l4jLKZvP-XKZF_1_3O1Q7T6kJP1N7dWaZyetjaawi35dqSQmEdmDA2vtuNPGi8Xl-LASE-uxcNJnMG_cuWODPFT_Tf7l72WSv-RKvQma3P8v4h_Avd7jRO-3IvIQbpn6EI6m_Ttli16j6Qit3B7C3dkI5No-gsnMLM7RvPn-DslN1_hh5Mc8zKIlAckOFRs1Mxq19rwNul5J1PeiuEJdg1xX-MewmJx9-nAe9a0X7JnFuIsqarBimeEVYSrJNFWSkNTaMcNL4_BkOJeKSFzRMqZE40wRbWJmZzGhOXkC-3VTm6eAFE91npZ5rkpNK-L6B6q0SqRh1l-24V4A8XAUouxRyV1zjK_CRyc8E1vWCcs64VgnSABvxi3ftpAcf1t86s53XOjQtP1As74SvXIKbS_8XCmpKhs80kpyY6gmPKtwbr2ZNA_geJAO0at4KxKeU-uLERIH8HKctsrpMi6yNs3GreE8T10AE8DRVphGSqxfkLicdwBsR8x2SN2dqVdfPAB46pzajAfwdhC2n8j6Eyee_dPq53AHe2mlUcKOYb9bb8wLuF1ed6t2HcIeWzL_5SEcnJ7Ni4vQv2aErna28N-FnSk-zorPodfPH6BSLNQ |
| linkProvider | Springer Nature |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB5VBQkuvCmBAkYCDqCoie3EDhJCvFZbdXdVqRXaE1YcO2UF2pRNthX_iR_J2JsElkdvPXCNHcmxP8_M53G-AXhccCak5TIsUqFDbrUOc5OUoWSxSRFCKfVVIj6MxGQip9NsfwO-d__CuGuVnU30htpUhTsj34llxtH1If1-dfw1dFWjXHa1K6GxgsWe_XaKlK1-ufsO1_cJpYP3h2-HYVtVAIcT0SYsuaVapFaWTOg4NVznjCVooq0srJNKkTLXLKclLyLODE01MzYS2EoZd9JLaPAvoBUX7gKZmIr-RCdiGCpJ1qZOY5nu1EgAqSPs7nYnZSFbc36-RsDfAts_72f-lqT1vm9w9f-atWtwpY2xyevVprgOG3Z-A7ZG7clsTZ6SUS8mXd-EwdgeDMmkOn1B8mVTeQ1b4p95KUmcEZI3ZH-px9aQGjFtycksJ229jSPSVAQd_udbcHAOn3QbNufV3N4BomVisqTIMl0YXjJXI1EnZZxbgZwAKW0AUbfqqmiV110BkC_KMzCZqhVQFAJFOaAoFsCz_pXjlezIWZ3fOCj1HZ1iuH9QLY5Ua4CUQaeWaZ3rEgkyL3NpLTdMpiXNMGJLsgC2OwSp1ozV6id8AnjUN6MBclmlfG6rpesjZZY4khbA1gq3_Ugw9oldXj8AsYbotaGut8xnn7zIeeIC91QG8LzD_i_D-tdM3D37Ix7CpeHheKRGu5O9e3CZ-o3Jw1hsw2azWNr7cLE4aWb14oHf2QQ-nu-W-AEI2oXA |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3di9QwEB_0FNEHP069q54aQXzwKNc2aZr45tdy4u6ysHLcW0ia5Fw42mPbPf99k_QDV09BfE0mME1-w8xk0t8AvCoJLpghLC5poWJilIqlzm3McKqpgxDNQpeIk2kxn7PTU77o-5w2w2v3oSTZ_dPgWZqq9uhC287EGT1qXGaV-UzYP5vMcIyvww3iewb5dH15Ml6yJNhFLwz31cwrV275o0Dbf1Ws-fuTyV_qpsEdTe7994fch7t9JIreddB5ANdMtQt70_7-skGv0XSkXG524c5sJHhtHsJkZpbHaF5_f4vkpq3DMApjgX7RqYNkixYbNTMaNQ4HBl2uJOp7VJyhtka-W_wjWE4-ff1wHPctGdxZJlkbW2IyVVDDLC5USjVREuPc-TfDSuN5ZhiTCsvMkjIhWGdUYW2Sws1mmHD8GHaqujL7gBTLNc9LzlWpicW-r6DKbSpN4eJolwZGkAzHIsqerdw3zTgXIWthVHRbJ9zWCb91AkfwZlxy0VF1_E34vT_rUdCzbIeBen0meqMV2jkCrpRU1iWVxEpmDNGYUZtxF-XkPIKDASmiN_1GpIwTF6NhnETwcpx2RusrMbIy9cbLMMZzn9hEsNcBa9TExQupr4VHUGxBbkvV7Zlq9S0Qg-c-2KUsgsMBeD-p9aedePJP0i_g1uLjREw_z788hdtZAC6J0-IAdtr1xjyDm-Vlu2rWz4Mh_gDvtDCf |
| 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=MeSH+Now%3A+automatic+MeSH+indexing+at+PubMed+scale+via+learning+to+rank&rft.jtitle=Journal+of+biomedical+semantics&rft.au=Mao%2C+Yuqing&rft.au=Lu%2C+Zhiyong&rft.date=2017-04-17&rft.pub=BioMed+Central&rft.eissn=2041-1480&rft.volume=8&rft_id=info:doi/10.1186%2Fs13326-017-0123-3&rft_id=info%3Apmid%2F28412964&rft.externalDocID=PMC5392968 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2041-1480&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2041-1480&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2041-1480&client=summon |