{"id":"https://openalex.org/W3003244993","doi":"https://doi.org/10.24406/publica-fhg-406560","title":"AI supported Topic Modeling using KNIME-Workflows","display_name":"AI supported Topic Modeling using KNIME-Workflows","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3003244993","doi":"https://doi.org/10.24406/publica-fhg-406560","mag":"3003244993"},"language":"en","primary_location":{"id":"pmh:oai:fraunhofer.de:N-575025","doi":null,"is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-575025.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FOKUS","raw_type":"conferenceObject"},"parent_works":[],"lineage":["https://openalex.org/W3003244993"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://publica.fraunhofer.de/documents/N-575025.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000776862","display_name":"Jamal Al Qundus","orcid":"https://orcid.org/0000-0002-8848-1632","observed_orcids":["https://orcid.org/0000-0002-8848-1632"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Al Qundus, Jamal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036814189","display_name":"Silvio Peikert","orcid":"https://orcid.org/0000-0001-5716-1540","observed_orcids":["https://orcid.org/0000-0001-5716-1540"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peikert, Silvio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088336451","display_name":"Adrian Paschke","orcid":"https://orcid.org/0000-0003-3156-9040","observed_orcids":["https://orcid.org/0000-0003-3156-9040"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paschke, Adrian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.753,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.73488131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.044199999421834946,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.004399999976158142,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/topic-modeling","display_name":"topic modeling","score":0.9390000104904175},{"id":"https://openalex.org/keywords/dbpedia","display_name":"DBpedia","score":0.6840000152587891},{"id":"https://openalex.org/keywords/dbpedia-spotlight","display_name":"DBpedia Spotlight","score":0.8399999737739563},{"id":"https://openalex.org/keywords/entity-linking","display_name":"entity linking","score":0.671999990940094},{"id":"https://openalex.org/keywords/knowledge-base-enrichment","display_name":"knowledge base enrichment","score":0.800000011920929},{"id":"https://openalex.org/keywords/knime-workflow","display_name":"KNIME workflow","score":0.6290000081062317},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"latent Dirichlet allocation","score":0.9309999942779541},{"id":"https://openalex.org/keywords/text-mining","display_name":"text mining","score":0.6620000004768372},{"id":"https://openalex.org/keywords/semantic-interpretation","display_name":"semantic interpretation","score":0.6320000290870667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8839022517204285},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7762778997421265},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.769556999206543},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6336593627929688},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5410354137420654},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5076528787612915},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.49073493480682373},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4389573335647583},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4189720153808594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3029744029045105},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11877003312110901},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:fraunhofer.de:N-575025","doi":null,"is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-575025.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FOKUS","raw_type":"conferenceObject"},{"id":"pmh:oai:publica.fraunhofer.de:publica/406560","doi":null,"is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/406560","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/501721","doi":null,"is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/501721","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"doi:10.24406/publica-fhg-406560","doi":"https://doi.org/10.24406/publica-fhg-406560","is_oa":true,"landing_page_url":"https://doi.org/10.24406/publica-fhg-406560","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:3003244993","doi":null,"is_oa":false,"landing_page_url":"http://ceur-ws.org/Vol-2535/paper_13.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:fraunhofer.de:N-575025","doi":null,"is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-575025.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FOKUS","raw_type":"conferenceObject"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1612003148","https://openalex.org/W1880262756","https://openalex.org/W1979900513","https://openalex.org/W2097807612","https://openalex.org/W2106490775","https://openalex.org/W2293301714","https://openalex.org/W2533331606","https://openalex.org/W2808709741"],"related_works":["https://openalex.org/W6903756517","https://openalex.org/W6960012027","https://openalex.org/W3108672326","https://openalex.org/W7223229991","https://openalex.org/W7215214106","https://openalex.org/W1953871010","https://openalex.org/W6906634030","https://openalex.org/W2941896711","https://openalex.org/W3030161640","https://openalex.org/W2935432477"],"abstract_inverted_index":{"Topic":[0],"modeling":[1,126,137],"algorithms":[2,144],"traditionally":[3],"model":[4],"topics":[5],"as":[6,28],"list":[7],"of":[8,41,46,53,68,77,124],"weighted":[9],"terms.":[10],"These":[11],"topic":[12,56,79,125,136],"models":[13,80],"can":[14],"be":[15,82],"used":[16,91,104],"effectively":[17],"to":[18,22,92,105,132],"classify":[19],"texts":[20],"or":[21,31],"support":[23],"text":[24,29,98],"mining":[25],"tasks":[26],"such":[27],"summarization":[30],"fact":[32],"extraction.":[33],"The":[34,44],"general":[35],"procedure":[36],"relies":[37],"on":[38,50,85],"statistical":[39],"analysis":[40],"term":[42],"frequencies.":[43],"focus":[45],"this":[47,117],"work":[48],"is":[49,90,103],"the":[51,54,69,74,96],"implementation":[52],"knowledge-based":[55],"modelling":[57],"services":[58],"in":[59,95,114],"a":[60,111,121],"KNIME2":[61],"workflow.":[62],"A":[63],"brief":[64],"description":[65],"and":[66,73,99,119,145],"evaluation":[67,76],"DBPedia3based":[70],"enrichment":[71],"approach":[72,118,138],"comparative":[75],"enriched":[78],"will":[81],"outlined":[83],"based":[84],"our":[86],"previous":[87],"work.":[88],"DBpedia-Spotlight4":[89],"identify":[93],"entities":[94],"input":[97],"information":[100,131],"from":[101],"DBpedia":[102],"extend":[106],"these":[107],"entities.":[108],"We":[109],"provide":[110],"workflow":[112],"developed":[113],"KNIME":[115],"implementing":[116],"perform":[120],"result":[122],"comparison":[123],"supported":[127],"by":[128,143,146],"knowledge":[129],"base":[130],"traditional":[133],"LDA.":[134],"This":[135],"allows":[139],"semantic":[140],"interpretation":[141],"both":[142],"humans.":[147]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2020-02-07T00:00:00"}