{"id":"https://openalex.org/W2129770922","doi":"https://doi.org/10.1142/s021800141559003x","title":"Document Representation with Statistical Word Senses in Cross-Lingual Document Clustering","display_name":"Document Representation with Statistical Word Senses in Cross-Lingual Document Clustering","publication_year":2014,"publication_date":"2014-10-24","ids":{"openalex":"https://openalex.org/W2129770922","doi":"https://doi.org/10.1142/s021800141559003x","mag":"2129770922"},"language":"en","primary_location":{"id":"doi:10.1142/s021800141559003x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800141559003x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5045596194","display_name":"Guoyu Tang","orcid":"https://orcid.org/0009-0003-9586-4652"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyu Tang","raw_affiliation_strings":["Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069555295","display_name":"Yunqing Xia","orcid":"https://orcid.org/0009-0005-8608-574X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunqing Xia","raw_affiliation_strings":["Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100752356","display_name":"Erik Cambria","orcid":"https://orcid.org/0000-0002-3030-1280"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Erik Cambria","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore","School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043790437","display_name":"Peng Jin","orcid":"https://orcid.org/0000-0002-4835-0312"},"institutions":[{"id":"https://openalex.org/I2802584641","display_name":"Leshan Normal University","ror":"https://ror.org/036cvz290","country_code":"CN","type":"education","lineage":["https://openalex.org/I2802584641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Jin","raw_affiliation_strings":["School of Computer Science, Leshan Normal University, Leshan 614000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Leshan Normal University, Leshan 614000, P. R. China","institution_ids":["https://openalex.org/I2802584641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084318285","display_name":"Thomas Fang Zheng","orcid":"https://orcid.org/0000-0002-0249-4767"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Thomas Fang Zheng","raw_affiliation_strings":["Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, TNList, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0709,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.89720439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"29","issue":"02","first_page":"1559003","last_page":"1559003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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":0.9983999729156494,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9977999925613403,"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/computer-science","display_name":"Computer science","score":0.8292186856269836},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7552610039710999},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.7232891917228699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6666991710662842},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.6497930288314819},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6142979860305786},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5874143838882446},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5070319175720215},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4723580777645111},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.4249008297920227},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.351701945066452},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10066625475883484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8292186856269836},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7552610039710999},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.7232891917228699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6666991710662842},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.6497930288314819},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6142979860305786},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5874143838882446},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5070319175720215},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4723580777645111},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.4249008297920227},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.351701945066452},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10066625475883484},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s021800141559003x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800141559003x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.725.2402","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.725.2402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cslt.riit.tsinghua.edu.cn/%7Efzheng/PAPERS/2015/1502E_IJPRAI_Doc-rep-with-statistical-word-senses-TGY.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5799999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W78284816","https://openalex.org/W1511480444","https://openalex.org/W1548506174","https://openalex.org/W1651093245","https://openalex.org/W1861576520","https://openalex.org/W1880262756","https://openalex.org/W1974406477","https://openalex.org/W1974578407","https://openalex.org/W1975084891","https://openalex.org/W1981257123","https://openalex.org/W1983578042","https://openalex.org/W1987562605","https://openalex.org/W1993001977","https://openalex.org/W2001082470","https://openalex.org/W2006177461","https://openalex.org/W2033593667","https://openalex.org/W2040683545","https://openalex.org/W2048592642","https://openalex.org/W2049449085","https://openalex.org/W2055103902","https://openalex.org/W2087743880","https://openalex.org/W2092094655","https://openalex.org/W2102471052","https://openalex.org/W2105588112","https://openalex.org/W2118013824","https://openalex.org/W2118909842","https://openalex.org/W2120779048","https://openalex.org/W2127365348","https://openalex.org/W2129984229","https://openalex.org/W2133517430","https://openalex.org/W2133576408","https://openalex.org/W2145631291","https://openalex.org/W2148172987","https://openalex.org/W2148861942","https://openalex.org/W2158266063","https://openalex.org/W2165612380","https://openalex.org/W2171566979","https://openalex.org/W2252209277","https://openalex.org/W2341587966","https://openalex.org/W2962684168","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W3005513013","https://openalex.org/W2207653751","https://openalex.org/W2611137333","https://openalex.org/W4309228610","https://openalex.org/W4294597112"],"abstract_inverted_index":{"Cross-lingual":[0],"document":[1,41,114],"clustering":[2,75],"is":[3,26],"the":[4,79,89,100,105],"task":[5],"of":[6,12],"automatically":[7,58],"organizing":[8],"a":[9,16,61,65,73,83,93],"large":[10],"collection":[11],"multi-lingual":[13],"documents":[14,51],"into":[15],"few":[17],"clusters,":[18],"depending":[19],"on":[20,92,99],"their":[21],"content":[22],"or":[23],"topic.":[24],"It":[25],"well":[27],"known":[28],"that":[29,104],"language":[30],"barrier":[31],"and":[32,72,88],"translation":[33],"ambiguity":[34],"are":[35,57],"two":[36,109],"challenging":[37],"issues":[38],"for":[39,112],"cross-lingual":[40,50,67,113],"representation.":[42],"To":[43],"this":[44],"end,":[45],"we":[46],"propose":[47],"to":[48],"represent":[49],"through":[52,64],"statistical":[53],"word":[54,68],"senses,":[55],"which":[56],"discovered":[59],"from":[60],"parallel":[62],"corpus":[63],"novel":[66],"sense":[69,74],"induction":[70],"model":[71,87],"method.":[76],"In":[77],"particular,":[78],"former":[80],"consists":[81],"in":[82],"sense-based":[84,94],"vector":[85],"space":[86],"latter":[90],"leverages":[91],"latent":[95],"Dirichlet":[96],"allocation.":[97],"Evaluation":[98],"benchmarking":[101],"datasets":[102],"shows":[103],"proposed":[106],"models":[107],"outperform":[108],"state-of-the-art":[110],"methods":[111],"clustering.":[115]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
