{"id":"https://openalex.org/W142195158","doi":"https://doi.org/10.1007/978-3-319-11397-5_14","title":"Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling","display_name":"Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W142195158","doi":"https://doi.org/10.1007/978-3-319-11397-5_14","mag":"142195158"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-11397-5_14","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-11397-5_14","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ris.utwente.nl/ws/files/5321913/chp_3A10.1007_2F978-3-319-11397-5_14.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054359571","display_name":"Zhemin Zhu","orcid":"https://orcid.org/0000-0003-0633-053X"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Zhemin Zhu","raw_affiliation_strings":["Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","Univ. of Twente#TAB#"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"Univ. of Twente#TAB#","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108167267","display_name":"Djoerd Hiemstra","orcid":"https://orcid.org/0000-0003-4967-2900"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Djoerd Hiemstra","raw_affiliation_strings":["Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","Univ. of Twente#TAB#"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"Univ. of Twente#TAB#","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091150744","display_name":"Peter M. G. Apers","orcid":null},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Peter Apers","raw_affiliation_strings":["Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","Univ. of Twente#TAB#"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"Univ. of Twente#TAB#","institution_ids":["https://openalex.org/I94624287"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054359571"],"corresponding_institution_ids":["https://openalex.org/I94624287"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.949,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6936601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/sequence-labeling","display_name":"Sequence labeling","score":0.9370704889297485},{"id":"https://openalex.org/keywords/crfs","display_name":"CRFS","score":0.9341235756874084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8151025772094727},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8025397062301636},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6174299716949463},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5908967852592468},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.576083242893219},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.46906185150146484},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4549609422683716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44991230964660645},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.41186007857322693},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35353171825408936},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33222663402557373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2940082550048828}],"concepts":[{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.9370704889297485},{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.9341235756874084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8151025772094727},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8025397062301636},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6174299716949463},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5908967852592468},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.576083242893219},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.46906185150146484},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4549609422683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44991230964660645},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.41186007857322693},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35353171825408936},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33222663402557373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2940082550048828},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-319-11397-5_14","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-11397-5_14","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:ris.utwente.nl:publications/de4a054b-4aed-4ef2-b450-41a2be37563a","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/de4a054b-4aed-4ef2-b450-41a2be37563a","pdf_url":"https://ris.utwente.nl/ws/files/5321913/chp_3A10.1007_2F978-3-319-11397-5_14.pdf","source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhu, Z, Hiemstra, D & Apers, P M G 2014, Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling. in Proceedings of the Second International Conference on Statistical Language and Speech Processing, SLSP 2014. Lecture Notes in Artifical Intelligence, vol. 8791, Springer, Berlin, pp. 185-196. https://doi.org/10.1007/978-3-319-11397-5_14","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:repository.ubn.ru.nl:2066/226885","is_oa":false,"landing_page_url":"https://hdl.handle.net/2066/226885","pdf_url":null,"source":{"id":"https://openalex.org/S4306401067","display_name":"Radboud Repository (Radboud University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145872427","host_organization_name":"Radboud University Nijmegen","host_organization_lineage":["https://openalex.org/I145872427"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Besacier, L. (ed.), Statistical Language and Speech Processing: Second International Conference, SLSP 2014, Grenoble, France, October 14-16, 2014, Proceedings, pp. 185-196","raw_type":"Article in monograph or in proceedings"}],"best_oa_location":{"id":"pmh:oai:ris.utwente.nl:publications/de4a054b-4aed-4ef2-b450-41a2be37563a","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/de4a054b-4aed-4ef2-b450-41a2be37563a","pdf_url":"https://ris.utwente.nl/ws/files/5321913/chp_3A10.1007_2F978-3-319-11397-5_14.pdf","source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhu, Z, Hiemstra, D & Apers, P M G 2014, Linear Co-occurrence Rate Networks (L-CRNs) for Sequence Labeling. in Proceedings of the Second International Conference on Statistical Language and Speech Processing, SLSP 2014. Lecture Notes in Artifical Intelligence, vol. 8791, Springer, Berlin, pp. 185-196. https://doi.org/10.1007/978-3-319-11397-5_14","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W142195158.pdf","grobid_xml":"https://content.openalex.org/works/W142195158.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W196969749","https://openalex.org/W1493509634","https://openalex.org/W1593045043","https://openalex.org/W1909733559","https://openalex.org/W1934019294","https://openalex.org/W1964357740","https://openalex.org/W1997319317","https://openalex.org/W2088692044","https://openalex.org/W2093135704","https://openalex.org/W2104029044","https://openalex.org/W2104321281","https://openalex.org/W2118585731","https://openalex.org/W2125838338","https://openalex.org/W2129999749","https://openalex.org/W2144068644","https://openalex.org/W2144578941","https://openalex.org/W2147880316","https://openalex.org/W2149684865","https://openalex.org/W2964316279","https://openalex.org/W3146331408","https://openalex.org/W4206192903"],"related_works":["https://openalex.org/W2122922410","https://openalex.org/W2102301788","https://openalex.org/W2158188757","https://openalex.org/W2131524408","https://openalex.org/W142195158","https://openalex.org/W2084282191","https://openalex.org/W2156161585","https://openalex.org/W3182785264","https://openalex.org/W3145683449","https://openalex.org/W3132721257"],"abstract_inverted_index":null,"counts_by_year":[{"year":2015,"cited_by_count":2}],"updated_date":"2026-03-17T17:19:04.345684","created_date":"2025-10-10T00:00:00"}