<TEI xmlns="http://www.tei-c.org/ns/1.0"><teiHeader><fileDesc><titleStmt><title>Episciences.org TEI export of elpub:4607 - ElPub - ELectronic PUBlishing, 2018-06-20, Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure</title></titleStmt><publicationStmt><distributor>CCSD - Episciences</distributor><availability status="restricted"><licence target="https://creativecommons.org/licenses/by/4.0">Attribution 4.0 International (CC BY 4.0)</licence></availability><date when="2018-06-20"/></publicationStmt><sourceDesc><p>Episciences.org API platform</p></sourceDesc></fileDesc></teiHeader><text><body><listBibl><biblFull><titleStmt><title xml:lang="en">Automatic Subject Indexing and Classification Using Text Recognition and Computer-Based Analysis of Tables of Contents</title><author role="aut"><persName><forename type="first">Jan</forename><surname>Pokorny</surname></persName><email/><affiliation ref="#struct-0"/></author></titleStmt><editionStmt><edition><date type="whenSubmitted">2018-06-20 21:22:57</date><date type="whenProduced">2018-06-20 21:57:28</date><ref type="file" target="http://elpub.episciences.org/4607/pdf"/></edition><respStmt><resp>contributor</resp><name key="630180"><persName><forename>OpenEdition</forename><surname>Press</surname></persName><email>press@openedition.org</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="id">elpub:4607</idno><idno type="url">http://elpub.episciences.org/4607</idno><idno type="ref">elpub:4607 - ElPub - ELectronic PUBlishing, 2018-06-20, Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure</idno><licence target="https://creativecommons.org/licenses/by/4.0">Attribution 4.0 International (CC BY 4.0)</licence></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Automatic Subject Indexing and Classification Using Text Recognition and Computer-Based Analysis of Tables of Contents</title><author role="aut"><persName><forename type="first">Jan</forename><surname>Pokorny</surname></persName><email/><affiliation ref="#struct-0"/></author></analytic><monogr><idno type="HAL">hal-01816705</idno><title level="j">ElPub - ELectronic PUBlishing</title><imprint><publisher/><biblScope unit="volume">Connecting the Knowledge Commons: From Projects to Sustainable Infrastructure</biblScope><biblScope unit="issue">Long Papers</biblScope><date type="datePub">2018-06-20T21:57:28+02:00</date></imprint></monogr><idno type="doi">10.4000/proceedings.elpub.2018.19</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term>machine learning system</term><term>computer-generated keywords</term><term>library automatization</term><term>text mining</term><term>computer-generated subject headings</term><term>[SHS.INFO]Humanities and Social Sciences/Library and information sciences</term></keywords></textClass><abstract><p>International audience</p></abstract><abstract xml:lang="en"><p>This paper will describe a method for machine-based creation of high quality subject indexing and classification for both electronic and print documents using tables of contents (ToCs). The technology described here is primarily focused on electronic and print documents for which, because of technical or licensing reasons, it is not possible to index full text. However, the technology would also be useful for full text documents, because it could significantly enhance the accuracy and relevance of subject description by analyzing the structure of ToCs.</p></abstract></profileDesc></biblFull></listBibl></body><back><listOrg><org xml:id="struct-0"><orgName>ENKI, o.p.s.</orgName></org></listOrg></back></text></TEI>