{"id":"https://openalex.org/W2252215444","doi":"https://doi.org/10.18653/v1/d15-1066","title":"LDTM: A Latent Document Type Model for Cumulative Citation Recommendation","display_name":"LDTM: A Latent Document Type Model for Cumulative Citation Recommendation","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2252215444","doi":"https://doi.org/10.18653/v1/d15-1066","mag":"2252215444"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d15-1066","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1066","pdf_url":"https://www.aclweb.org/anthology/D15-1066.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D15-1066.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100695181","display_name":"Jingang Wang","orcid":"https://orcid.org/0000-0002-2999-3371"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingang Wang","raw_affiliation_strings":["School of Computer Science, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039153635","display_name":"Dandan Song","orcid":"https://orcid.org/0000-0002-7239-6900"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Song","raw_affiliation_strings":["School of Computer Science, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347585","display_name":"Zhiwei Zhang","orcid":"https://orcid.org/0000-0001-6455-6866"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiwei Zhang","raw_affiliation_strings":["Dept. of Computer Science, Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044196762","display_name":"Lejian Liao","orcid":"https://orcid.org/0000-0003-1412-8243"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lejian Liao","raw_affiliation_strings":["School of Computer Science, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101718341","display_name":"Luo Si","orcid":"https://orcid.org/0000-0002-3263-234X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luo Si","raw_affiliation_strings":["Dept. of Computer Science, Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090151187","display_name":"Chin-Yew Lin","orcid":"https://orcid.org/0000-0002-0798-6365"},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chin-Yew Lin","raw_affiliation_strings":["Knowledge Mining Group, Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Knowledge Mining Group, Microsoft Research","institution_ids":["https://openalex.org/I4210124949"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044196762"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"561","last_page":"566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9984999895095825,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9958000183105469,"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/discriminative-model","display_name":"Discriminative model","score":0.8173838257789612},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7753223180770874},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.694589376449585},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5728889107704163},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5359156131744385},{"id":"https://openalex.org/keywords/citation","display_name":"Citation","score":0.496584951877594},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4222905933856964},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4113759696483612},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39867687225341797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36955726146698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33563512563705444},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.117276132106781},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06214421987533569}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8173838257789612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7753223180770874},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.694589376449585},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5728889107704163},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5359156131744385},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.496584951877594},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4222905933856964},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4113759696483612},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39867687225341797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36955726146698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33563512563705444},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.117276132106781},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06214421987533569},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/d15-1066","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1066","pdf_url":"https://www.aclweb.org/anthology/D15-1066.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.6676","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.6676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D15/D15-1066.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/d15-1066","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1066","pdf_url":"https://www.aclweb.org/anthology/D15-1066.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1173194731","display_name":"\u57fa\u4e8e\u77ed\u6587\u672c\u7684\u77e5\u8bc6\u5e93\u81ea\u52a8\u66f4\u65b0\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61472040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1828425977","display_name":null,"funder_award_id":"973 Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2118282207","display_name":null,"funder_award_id":"YETP1198","funder_id":"https://openalex.org/F4320335442","funder_display_name":"Beijing Higher Education Young Elite Teacher Project"},{"id":"https://openalex.org/G2590887055","display_name":null,"funder_award_id":"2013CB329600","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3752301980","display_name":null,"funder_award_id":"2013CB329600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8471755968","display_name":"\u57fa\u4e8e\u7ea6\u675f\u89c4\u5212\u7684\u8bed\u4e49Web\u670d\u52a1\u52a8\u6001\u7ec4\u5408\u6280\u672f\u7814\u7a76","funder_award_id":"60873237","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335442","display_name":"Beijing Higher Education Young Elite Teacher Project","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2252215444.pdf","grobid_xml":"https://content.openalex.org/works/W2252215444.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W62311994","https://openalex.org/W216536535","https://openalex.org/W614509546","https://openalex.org/W1964031635","https://openalex.org/W1980882427","https://openalex.org/W2000231972","https://openalex.org/W2020660727","https://openalex.org/W2038227503","https://openalex.org/W2125135708","https://openalex.org/W2295420380","https://openalex.org/W2395265779","https://openalex.org/W2406219572"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W2981954115"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"Cumulative":[3],"Citation":[4],"Recommendation":[5],"(CCR)":[6],"-given":[7],"an":[8],"entity":[9],"in":[10,39,45,125],"Knowledge":[11],"Bases,":[12],"how":[13],"to":[14,33,68,83,130],"effectively":[15],"detect":[16],"its":[17],"potential":[18],"citations":[19],"from":[20],"volume":[21],"text":[22],"streams.":[23],"Most":[24],"previous":[25],"approaches":[26],"treated":[27],"all":[28],"kinds":[29],"of":[30,86,98,104],"features":[31],"indifferently":[32],"build":[34],"a":[35,57,65,95,121],"global":[36],"relevance":[37],"model,":[38],"which":[40],"the":[41,70,113,131],"prior":[42],"knowledge":[43],"embedded":[44],"documents":[46,73,87],"cannot":[47],"be":[48],"exploited":[49],"adequately.":[50],"To":[51],"address":[52],"this":[53,117],"problem,":[54],"we":[55],"propose":[56],"latent":[58,66],"document":[59,99],"type":[60],"discriminative":[61],"model":[62,79,118],"by":[63],"introducing":[64],"layer":[67],"capture":[69],"correlations":[71],"between":[72],"and":[74,88,112],"their":[75],"underlying":[76],"types.":[77,100],"The":[78],"can":[80,119],"better":[81],"adjust":[82],"different":[84],"types":[85],"yield":[89,120],"flexible":[90],"performance":[91,123],"when":[92],"dealing":[93],"with":[94],"broad":[96],"range":[97],"An":[101],"extensive":[102],"set":[103],"experiments":[105],"has":[106],"been":[107],"conducted":[108],"on":[109],"TREC-KBA-2013":[110],"dataset,":[111],"results":[114],"demonstrate":[115],"that":[116],"significant":[122],"gain":[124],"recommendation":[126],"quality":[127],"as":[128],"compared":[129],"state-of-the-art.":[132]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-27T08:26:11.824852","created_date":"2025-10-10T00:00:00"}