{"id":"https://openalex.org/W2135848058","doi":"https://doi.org/10.1109/nlpke.2008.4906752","title":"Recognizing location names from Chinese texts based on Max-Margin Markov Network","display_name":"Recognizing location names from Chinese texts based on Max-Margin Markov Network","publication_year":2008,"publication_date":"2008-10-01","ids":{"openalex":"https://openalex.org/W2135848058","doi":"https://doi.org/10.1109/nlpke.2008.4906752","mag":"2135848058"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2008.4906752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2008.4906752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082868235","display_name":"Lishuang Li","orcid":"https://orcid.org/0000-0002-4189-1466"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lishuang Li","raw_affiliation_strings":["Dalian University of Technology, Dalian, Liaoning, China","Dalian University of Technology, Dalian)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"Dalian University of Technology, Dalian)","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008043408","display_name":"Zhuoye Ding","orcid":"https://orcid.org/0000-0001-7430-5980"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoye Ding","raw_affiliation_strings":["Dalian University of Technology, Dalian, Liaoning, China","Dalian University of Technology, Dalian)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"Dalian University of Technology, Dalian)","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046871248","display_name":"Degen Huang","orcid":"https://orcid.org/0000-0002-8860-7805"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degen Huang","raw_affiliation_strings":["Dalian University of Technology, Dalian, Liaoning, China","Dalian University of Technology, Dalian)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"Dalian University of Technology, Dalian)","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.5878,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79693886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9958999752998352,"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/crfs","display_name":"CRFS","score":0.7998855113983154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6623941659927368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5969580411911011},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5888494253158569},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5817002058029175},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5709402561187744},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5526981353759766},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.499420166015625},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4926784634590149},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.46454739570617676},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.4530581533908844},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.43693429231643677},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4309290051460266},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2848992347717285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23790189623832703},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18970748782157898},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1760769784450531}],"concepts":[{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.7998855113983154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6623941659927368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5969580411911011},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5888494253158569},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5817002058029175},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5709402561187744},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5526981353759766},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.499420166015625},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4926784634590149},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.46454739570617676},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.4530581533908844},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.43693429231643677},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4309290051460266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2848992347717285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23790189623832703},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18970748782157898},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1760769784450531},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2008.4906752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2008.4906752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W182104056","https://openalex.org/W1512098439","https://openalex.org/W2001831858","https://openalex.org/W2063287522","https://openalex.org/W2091812280","https://openalex.org/W2105644991","https://openalex.org/W2116317530","https://openalex.org/W2140016149","https://openalex.org/W2141099517","https://openalex.org/W2147880316","https://openalex.org/W2148603752","https://openalex.org/W2152463966","https://openalex.org/W2153104898","https://openalex.org/W2156909104","https://openalex.org/W2157791002","https://openalex.org/W2160735413","https://openalex.org/W2166561786","https://openalex.org/W2352455899","https://openalex.org/W2355769480","https://openalex.org/W2359171347","https://openalex.org/W2381198996","https://openalex.org/W3004533406","https://openalex.org/W4312326823","https://openalex.org/W6630527977","https://openalex.org/W6675760969","https://openalex.org/W6682082992","https://openalex.org/W6682238262","https://openalex.org/W6682953061","https://openalex.org/W7042795896"],"related_works":["https://openalex.org/W2055466819","https://openalex.org/W50079190","https://openalex.org/W2356597680","https://openalex.org/W182104056","https://openalex.org/W2111726165","https://openalex.org/W2011251309","https://openalex.org/W2796133761","https://openalex.org/W3088215229","https://openalex.org/W2511246383","https://openalex.org/W2184553228"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,74],"novel":[4],"method":[5],"of":[6],"recognizing":[7],"location":[8,79],"names":[9],"from":[10],"Chinese":[11],"texts":[12],"based":[13,98,111],"on":[14,99,112,120],"max-margin":[15],"Markov":[16],"<sub":[17],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[18,23,103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N</sub>":[19],"etwork":[20],"(M":[21],"<sup":[22,102],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>":[24,104],"Net)":[25],"owing":[26],"to":[27,30,96],"its":[28],"ability":[29],"exploit":[31],"very":[32],"high":[33],"dimensional":[34],"feature":[35],"spaces":[36],"(using":[37],"the":[38,43,64,71,78,90],"kernel":[39],"trick)":[40],"while":[41],"at":[42],"same":[44],"time":[45],"dealing":[46],"with":[47,51],"structured":[48],"data":[49],"compared":[50],"Support":[52],"Vector":[53],"Machine":[54],"(SVM)":[55],"and":[56,84],"conditional":[57],"random":[58],"fields":[59],"(CRFs).":[60],"In":[61],"our":[62],"model,":[63],"character":[65,75],"itself,":[66],"character-based":[67],"part-of-speech":[68],"(POS)":[69],"tag,":[70],"information":[72,86],"whether":[73],"appears":[76],"in":[77,117],"name":[80],"characteristic":[81],"word":[82],"table":[83],"context":[85],"are":[87],"extracted":[88],"as":[89],"features.":[91],"The":[92],"F-measure":[93],"is":[94,107],"up":[95],"90.57%":[97],"1-order":[100],"M":[101],"Net":[105],"which":[106],"better":[108],"than":[109],"that":[110],"either":[113],"SVM":[114],"or":[115],"CRFs":[116],"open":[118],"test":[119],"MSRA":[121],"dataset.":[122]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}