{"id":"https://openalex.org/W4306317414","doi":"https://doi.org/10.1145/3511808.3557573","title":"CStory: A Chinese Large-scale News Storyline Dataset","display_name":"CStory: A Chinese Large-scale News Storyline Dataset","publication_year":2022,"publication_date":"2022-10-15","ids":{"openalex":"https://openalex.org/W4306317414","doi":"https://doi.org/10.1145/3511808.3557573"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557573","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557573","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557573","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557573","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070811327","display_name":"Kaijie Shi","orcid":null},"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":true,"raw_author_name":"Kaijie Shi","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100775958","display_name":"Xiaozhi Wang","orcid":"https://orcid.org/0000-0002-5727-143X"},"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":"Xiaozhi Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038246814","display_name":"Jifan Yu","orcid":"https://orcid.org/0000-0003-3430-4048"},"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":"Jifan Yu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060498828","display_name":"Lei Hou","orcid":"https://orcid.org/0000-0002-8907-3526"},"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":"Lei Hou","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003324011","display_name":"Juanzi Li","orcid":"https://orcid.org/0000-0002-6244-0664"},"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":"Juanzi Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050928449","display_name":"Jingtong Wu","orcid":"https://orcid.org/0009-0004-3517-7452"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingtong Wu","raw_affiliation_strings":["Beijing Huawei Digital Technologies Co., Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Huawei Digital Technologies Co., Ltd., Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110347444","display_name":"Dingyu Yong","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingyu Yong","raw_affiliation_strings":["Huawei Device Co., Ltd., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Device Co., Ltd., Nanjing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102481665","display_name":"Jinghui Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghui Xiao","raw_affiliation_strings":["Huawei Noah's Ark Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426170","display_name":"Qun Liu","orcid":"https://orcid.org/0000-0002-7000-1792"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qun Liu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Hong Kong, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5070811327"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11118293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"4475","last_page":"4479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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":0.9979000091552734,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9660000205039978,"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":0.8649435043334961},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6251170039176941},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6048601269721985},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5933727622032166},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5722514986991882},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5206565260887146},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.502769947052002},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.48391658067703247},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43351301550865173},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.42319774627685547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26206135749816895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8649435043334961},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6251170039176941},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6048601269721985},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5933727622032166},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5722514986991882},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5206565260887146},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.502769947052002},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.48391658067703247},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43351301550865173},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.42319774627685547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26206135749816895},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557573","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557573","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557573","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3511808.3557573","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557573","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557573","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306317414.pdf","grobid_xml":"https://content.openalex.org/works/W4306317414.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1991018417","https://openalex.org/W2015488270","https://openalex.org/W2044222399","https://openalex.org/W2045784551","https://openalex.org/W2052408961","https://openalex.org/W2065427498","https://openalex.org/W2082105757","https://openalex.org/W2147674242","https://openalex.org/W2153679868","https://openalex.org/W2169343523","https://openalex.org/W2171317718","https://openalex.org/W2251282666","https://openalex.org/W2251471447","https://openalex.org/W2555366702","https://openalex.org/W2563936462","https://openalex.org/W2585731554","https://openalex.org/W2593831809","https://openalex.org/W2768070595","https://openalex.org/W2891455222","https://openalex.org/W2913248700","https://openalex.org/W2952370363","https://openalex.org/W3103818765","https://openalex.org/W4293547730"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2361861616","https://openalex.org/W2366107444","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W4388145910","https://openalex.org/W2358755282","https://openalex.org/W2032548952"],"abstract_inverted_index":{"In":[0],"today's":[1],"massive":[2],"news":[3,29,50,70,85,105,111,139],"streams,":[4],"storylines":[5,51,140],"can":[6],"help":[7],"us":[8],"discover":[9],"related":[10],"event":[11],"pairs":[12,86],"and":[13,43,90,119,135],"understand":[14],"the":[15,32,41,67,94,152,163],"evolution":[16],"of":[17,34,45,61,69,165],"hot":[18],"events.":[19,71],"Hence":[20],"many":[21],"efforts":[22],"have":[23],"been":[24],"devoted":[25],"to":[26,54,82],"automatically":[27],"constructing":[28,138],"storylines.":[30],"However,":[31],"development":[33],"these":[35,74],"methods":[36],"is":[37,141,170],"strongly":[38],"limited":[39],"by":[40,87],"size":[42],"quality":[44],"existing":[46],"storyline":[47,106,116],"datasets":[48],"since":[49],"are":[52],"expensive":[53],"annotate":[55],"as":[56],"they":[57],"contain":[58],"a":[59,78,102],"myriad":[60],"unlabeled":[62],"relationships":[63],"growing":[64],"quadratically":[65],"with":[66],"number":[68],"Working":[72],"around":[73],"difficulties,":[75],"we":[76,99],"propose":[77],"sophisticated":[79],"pre-processing":[80],"method":[81],"filter":[83,95],"candidate":[84],"entity":[88],"co-occurrence":[89],"semantic":[91],"similarity.":[92],"With":[93],"reducing":[96],"annotation":[97,124],"overhead,":[98],"construct":[100],"CStory,":[101],"large-scale":[103],"Chinese":[104],"dataset,":[107],"which":[108,160],"contains":[109],"11,978":[110],"articles,":[112],"112,549":[113],"manually":[114],"labeled":[115],"relation":[117],"pairs,":[118],"49,832":[120],"evidence":[121],"sentences":[122],"for":[123,144],"judgment.":[125],"We":[126],"conduct":[127],"extensive":[128],"experiments":[129],"on":[130],"CStory":[131],"using":[132],"various":[133],"algorithms":[134],"find":[136],"that":[137,151],"challenging":[142],"even":[143],"pre-trained":[145],"language":[146],"models.":[147],"Empirical":[148],"analysis":[149],"shows":[150],"sample":[153],"unbalance":[154],"issue":[155],"significantly":[156],"influences":[157],"model":[158],"performance,":[159],"shall":[161],"be":[162],"focus":[164],"future":[166],"works.":[167],"Our":[168],"dataset":[169],"now":[171],"publicly":[172],"available":[173],"at":[174],"https://github.com/THU-KEG/CStory.":[175]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
