A taxonomy generation tool for semantic visual analysis of large corpus of documents
Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by ext...
Gespeichert in:
Veröffentlicht in: | Multimedia tools and applications 2019-12, Vol.78 (23), p.32919-32937 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 32937 |
---|---|
container_issue | 23 |
container_start_page | 32919 |
container_title | Multimedia tools and applications |
container_volume | 78 |
creator | Carrion, Belen Onorati, Teresa Díaz, Paloma Triga, Vasiliki |
description | Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by extracting knowledge from large and unstructured data sets. Taxonomies are related to specific domains of knowledge in which they identify relevant topics. However, they have to be validated by experts to guarantee that its terms and relations are meaningful. In this paper, we introduce a semiautomatic taxonomy generation tool for supporting domain experts in building taxonomies that are then used to automatically create semantic visualizations of data. Our proposal combines automatic techniques to extract, sort and categorize terms, and empowers domain experts to take part at any stage of the process by providing a visual edition tool. We tested the tool’s usability in two use cases from different domains and languages. Results show that all the functionalities are easy to use and interact with. Lessons learned from this experience will guide the design of a utility evaluation involving domain experts interested in data analysis and knowledge modeling. |
doi_str_mv | 10.1007/s11042-019-07880-y |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2250342019</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2250342019</sourcerecordid><originalsourceid>FETCH-LOGICAL-c406t-2086521ce9024d177a53336b5cae35b3ea56139be0d6a930ce056111529b62243</originalsourceid><addsrcrecordid>eNp9kE9LxDAQxYMouK5-AU8Bz9WZpGm2x2XxHyx4Wc8hTdOlS9usSSr22xu3gjdPM_N4b3j8CLlFuEcA-RAQIWcZYJmBXK0gm87IAoXkmZQMz9POkygF4CW5CuEAgIVg-YLs1jTqLze4fqJ7O1ivY-sGGp3raOM8DbbXQ2wN_WzDqDuqB91NoQ3UNbTTfm-pcf44nu7ambG3QwzX5KLRXbA3v3NJ3p8ed5uXbPv2_LpZbzOTQxEzBqtUAo0tgeU1SqkF57yohNGWi4pbLQrkZWWhLnTJwVhIAqJgZVUwlvMluZv_Hr37GG2I6uBGnxoGxZgAnrMEJLnY7DLeheBto46-7bWfFIL6oadmeiqZ1YmemlKIz6GQzMPe-r_X_6S-ASnuckw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2250342019</pqid></control><display><type>article</type><title>A taxonomy generation tool for semantic visual analysis of large corpus of documents</title><source>SpringerNature Journals</source><creator>Carrion, Belen ; Onorati, Teresa ; Díaz, Paloma ; Triga, Vasiliki</creator><creatorcontrib>Carrion, Belen ; Onorati, Teresa ; Díaz, Paloma ; Triga, Vasiliki</creatorcontrib><description>Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by extracting knowledge from large and unstructured data sets. Taxonomies are related to specific domains of knowledge in which they identify relevant topics. However, they have to be validated by experts to guarantee that its terms and relations are meaningful. In this paper, we introduce a semiautomatic taxonomy generation tool for supporting domain experts in building taxonomies that are then used to automatically create semantic visualizations of data. Our proposal combines automatic techniques to extract, sort and categorize terms, and empowers domain experts to take part at any stage of the process by providing a visual edition tool. We tested the tool’s usability in two use cases from different domains and languages. Results show that all the functionalities are easy to use and interact with. Lessons learned from this experience will guide the design of a utility evaluation involving domain experts interested in data analysis and knowledge modeling.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-019-07880-y</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Computer Communication Networks ; Computer Science ; Data analysis ; Data Structures and Information Theory ; Domains ; Multimedia Information Systems ; Semantics ; Special Purpose and Application-Based Systems ; Subject specialists ; Taxonomy ; Unstructured data</subject><ispartof>Multimedia tools and applications, 2019-12, Vol.78 (23), p.32919-32937</ispartof><rights>The Author(s) 2019</rights><rights>Multimedia Tools and Applications is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c406t-2086521ce9024d177a53336b5cae35b3ea56139be0d6a930ce056111529b62243</citedby><cites>FETCH-LOGICAL-c406t-2086521ce9024d177a53336b5cae35b3ea56139be0d6a930ce056111529b62243</cites><orcidid>0000-0002-3154-249X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-019-07880-y$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-019-07880-y$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,27929,27930,41493,42562,51324</link.rule.ids></links><search><creatorcontrib>Carrion, Belen</creatorcontrib><creatorcontrib>Onorati, Teresa</creatorcontrib><creatorcontrib>Díaz, Paloma</creatorcontrib><creatorcontrib>Triga, Vasiliki</creatorcontrib><title>A taxonomy generation tool for semantic visual analysis of large corpus of documents</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by extracting knowledge from large and unstructured data sets. Taxonomies are related to specific domains of knowledge in which they identify relevant topics. However, they have to be validated by experts to guarantee that its terms and relations are meaningful. In this paper, we introduce a semiautomatic taxonomy generation tool for supporting domain experts in building taxonomies that are then used to automatically create semantic visualizations of data. Our proposal combines automatic techniques to extract, sort and categorize terms, and empowers domain experts to take part at any stage of the process by providing a visual edition tool. We tested the tool’s usability in two use cases from different domains and languages. Results show that all the functionalities are easy to use and interact with. Lessons learned from this experience will guide the design of a utility evaluation involving domain experts interested in data analysis and knowledge modeling.</description><subject>Computer Communication Networks</subject><subject>Computer Science</subject><subject>Data analysis</subject><subject>Data Structures and Information Theory</subject><subject>Domains</subject><subject>Multimedia Information Systems</subject><subject>Semantics</subject><subject>Special Purpose and Application-Based Systems</subject><subject>Subject specialists</subject><subject>Taxonomy</subject><subject>Unstructured data</subject><issn>1380-7501</issn><issn>1573-7721</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kE9LxDAQxYMouK5-AU8Bz9WZpGm2x2XxHyx4Wc8hTdOlS9usSSr22xu3gjdPM_N4b3j8CLlFuEcA-RAQIWcZYJmBXK0gm87IAoXkmZQMz9POkygF4CW5CuEAgIVg-YLs1jTqLze4fqJ7O1ivY-sGGp3raOM8DbbXQ2wN_WzDqDuqB91NoQ3UNbTTfm-pcf44nu7ambG3QwzX5KLRXbA3v3NJ3p8ed5uXbPv2_LpZbzOTQxEzBqtUAo0tgeU1SqkF57yohNGWi4pbLQrkZWWhLnTJwVhIAqJgZVUwlvMluZv_Hr37GG2I6uBGnxoGxZgAnrMEJLnY7DLeheBto46-7bWfFIL6oadmeiqZ1YmemlKIz6GQzMPe-r_X_6S-ASnuckw</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Carrion, Belen</creator><creator>Onorati, Teresa</creator><creator>Díaz, Paloma</creator><creator>Triga, Vasiliki</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-3154-249X</orcidid></search><sort><creationdate>20191201</creationdate><title>A taxonomy generation tool for semantic visual analysis of large corpus of documents</title><author>Carrion, Belen ; Onorati, Teresa ; Díaz, Paloma ; Triga, Vasiliki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c406t-2086521ce9024d177a53336b5cae35b3ea56139be0d6a930ce056111529b62243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Computer Communication Networks</topic><topic>Computer Science</topic><topic>Data analysis</topic><topic>Data Structures and Information Theory</topic><topic>Domains</topic><topic>Multimedia Information Systems</topic><topic>Semantics</topic><topic>Special Purpose and Application-Based Systems</topic><topic>Subject specialists</topic><topic>Taxonomy</topic><topic>Unstructured data</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Carrion, Belen</creatorcontrib><creatorcontrib>Onorati, Teresa</creatorcontrib><creatorcontrib>Díaz, Paloma</creatorcontrib><creatorcontrib>Triga, Vasiliki</creatorcontrib><collection>Springer Nature OA/Free Journals</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Multimedia tools and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Carrion, Belen</au><au>Onorati, Teresa</au><au>Díaz, Paloma</au><au>Triga, Vasiliki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A taxonomy generation tool for semantic visual analysis of large corpus of documents</atitle><jtitle>Multimedia tools and applications</jtitle><stitle>Multimed Tools Appl</stitle><date>2019-12-01</date><risdate>2019</risdate><volume>78</volume><issue>23</issue><spage>32919</spage><epage>32937</epage><pages>32919-32937</pages><issn>1380-7501</issn><eissn>1573-7721</eissn><abstract>Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by extracting knowledge from large and unstructured data sets. Taxonomies are related to specific domains of knowledge in which they identify relevant topics. However, they have to be validated by experts to guarantee that its terms and relations are meaningful. In this paper, we introduce a semiautomatic taxonomy generation tool for supporting domain experts in building taxonomies that are then used to automatically create semantic visualizations of data. Our proposal combines automatic techniques to extract, sort and categorize terms, and empowers domain experts to take part at any stage of the process by providing a visual edition tool. We tested the tool’s usability in two use cases from different domains and languages. Results show that all the functionalities are easy to use and interact with. Lessons learned from this experience will guide the design of a utility evaluation involving domain experts interested in data analysis and knowledge modeling.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11042-019-07880-y</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-3154-249X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1380-7501 |
ispartof | Multimedia tools and applications, 2019-12, Vol.78 (23), p.32919-32937 |
issn | 1380-7501 1573-7721 |
language | eng |
recordid | cdi_proquest_journals_2250342019 |
source | SpringerNature Journals |
subjects | Computer Communication Networks Computer Science Data analysis Data Structures and Information Theory Domains Multimedia Information Systems Semantics Special Purpose and Application-Based Systems Subject specialists Taxonomy Unstructured data |
title | A taxonomy generation tool for semantic visual analysis of large corpus of documents |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-14T08%3A23%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20taxonomy%20generation%20tool%20for%20semantic%20visual%20analysis%20of%20large%20corpus%20of%20documents&rft.jtitle=Multimedia%20tools%20and%20applications&rft.au=Carrion,%20Belen&rft.date=2019-12-01&rft.volume=78&rft.issue=23&rft.spage=32919&rft.epage=32937&rft.pages=32919-32937&rft.issn=1380-7501&rft.eissn=1573-7721&rft_id=info:doi/10.1007/s11042-019-07880-y&rft_dat=%3Cproquest_cross%3E2250342019%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2250342019&rft_id=info:pmid/&rfr_iscdi=true |