{"id":"https://openalex.org/W2168286517","doi":"https://doi.org/10.1145/1183614.1183713","title":"Document re-ranking using cluster validation and label propagation","display_name":"Document re-ranking using cluster validation and label propagation","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2168286517","doi":"https://doi.org/10.1145/1183614.1183713","mag":"2168286517"},"language":"en","primary_location":{"id":"doi:10.1145/1183614.1183713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1183614.1183713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM international conference on Information and knowledge management  - CIKM '06","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/A5052515692","display_name":"Lingpeng Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Lingpeng Yang","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106672007","display_name":"Donghong Ji","orcid":"https://orcid.org/0000-0002-9510-6726"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Donghong Ji","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012794465","display_name":"Guodong Zhou","orcid":"https://orcid.org/0000-0002-7887-5099"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Guodong Zhou","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101523267","display_name":"Yu Nie","orcid":"https://orcid.org/0000-0003-4891-1877"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yu Nie","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100958767","display_name":"Guozheng Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozheng Xiao","raw_affiliation_strings":["Wuhan University, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052515692"],"corresponding_institution_ids":["https://openalex.org/I3005327000"],"apc_list":null,"apc_paid":null,"fwci":6.0477,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.96140027,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"690","last_page":"690"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9991999864578247,"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":0.9991999864578247,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9962999820709229,"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/ranking","display_name":"Ranking (information retrieval)","score":0.8596137166023254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8306783437728882},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6962348818778992},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6691509485244751},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6512465476989746},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5912266373634338},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.5466648936271667},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4704400897026062},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.467357873916626},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.43170350790023804},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.41076067090034485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4025109112262726},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.14096540212631226}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.8596137166023254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8306783437728882},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6962348818778992},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6691509485244751},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6512465476989746},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5912266373634338},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.5466648936271667},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4704400897026062},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.467357873916626},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.43170350790023804},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.41076067090034485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4025109112262726},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.14096540212631226},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1183614.1183713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1183614.1183713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM international conference on Information and knowledge management  - CIKM '06","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.672.8482","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.672.8482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://nlp.suda.edu.cn/%7Egdzhou/publication/yanglp2006_CIKM_LPbasedDocumentReranking.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5099999904632568,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1509769683","https://openalex.org/W1522361370","https://openalex.org/W1630959083","https://openalex.org/W1979459060","https://openalex.org/W1999817920","https://openalex.org/W2002306339","https://openalex.org/W2028122423","https://openalex.org/W2056206543","https://openalex.org/W2058553017","https://openalex.org/W2063490066","https://openalex.org/W2090570708","https://openalex.org/W2098034778","https://openalex.org/W2114098461","https://openalex.org/W2122837498","https://openalex.org/W2126184790","https://openalex.org/W2127358574","https://openalex.org/W2130395434","https://openalex.org/W2139823104","https://openalex.org/W2146950091","https://openalex.org/W2158201212","https://openalex.org/W2399033236","https://openalex.org/W2789506669"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907","https://openalex.org/W25098770"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,15,67,86],"novel":[4],"document":[5,30],"re-ranking":[6],"approach":[7,45,113],"in":[8,27,42],"information":[9],"retrieval,":[10],"which":[11],"is":[12],"done":[13],"by":[14],"label":[16,104],"propagation-based":[17],"semi-supervised":[18],"learning":[19],"algorithm":[20],"to":[21,47],"utilize":[22],"the":[23,28,54,58,72,91,95,98,112],"intrinsic":[24],"structure":[25],"underlying":[26],"large":[29],"data.":[31],"Since":[32],"no":[33],"labeled":[34,51],"relevant":[35,63],"or":[36],"irrelevant":[37,82],"documents":[38,52,70,89,99],"are":[39],"generally":[40],"available":[41],"IR,":[43],"our":[44],"tries":[46],"extract":[48],"some":[49],"pseudo":[50,62,81],"from":[53,71,90],"ranking":[55,96],"list":[56],"of":[57,69,88,97],"initial":[59],"retrieval.":[60],"For":[61],"documents,":[64],"we":[65,84],"determine":[66],"cluster":[68,76],"top":[73],"ones":[74],"via":[75,103],"validation-based":[77],"k-means":[78],"clustering;":[79],"for":[80],"ones,":[83],"pick":[85],"set":[87],"bottom":[92],"ones.":[93],"Then":[94],"can":[100,114],"be":[101],"conducted":[102],"propagation.":[105],"Evaluation":[106],"on":[107],"benchmark":[108],"corpora":[109],"shows":[110],"that":[111],"achieve":[115],"significant":[116],"improvement":[117],"over":[118],"standard":[119],"baselines":[120],"and":[121],"performs":[122],"better":[123],"than":[124],"other":[125],"related":[126],"approaches.":[127]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}