{"id":"https://openalex.org/W4306317435","doi":"https://doi.org/10.1145/3511808.3557561","title":"CNewsTS - A Large-scale Chinese News Dataset with Hierarchical Topic Category and Summary","display_name":"CNewsTS - A Large-scale Chinese News Dataset with Hierarchical Topic Category and Summary","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317435","doi":"https://doi.org/10.1145/3511808.3557561"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557561","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557561","pdf_url":null,"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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048436051","display_name":"Quanzhi Li","orcid":"https://orcid.org/0000-0002-4605-4237"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quanzhi Li","raw_affiliation_strings":["Tencent, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011823804","display_name":"Yingchi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingchi Liu","raw_affiliation_strings":["Yohana, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yohana, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101667989","display_name":"Yang Chao","orcid":"https://orcid.org/0000-0002-2697-5661"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Chao","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.390625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4193","last_page":"4198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.9970999956130981,"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"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.9970999956130981,"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":0.9965999722480774,"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":0.9962000250816345,"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":0.6738936901092529},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6094571948051453},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4726763367652893},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3806314766407013},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3267323970794678},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1397094428539276},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07617759704589844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6738936901092529},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6094571948051453},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4726763367652893},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3806314766407013},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3267323970794678},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1397094428539276},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07617759704589844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557561","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557561","pdf_url":null,"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":null,"license_id":null,"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":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1491576965","https://openalex.org/W1544827683","https://openalex.org/W1552847225","https://openalex.org/W1781770377","https://openalex.org/W1840435438","https://openalex.org/W1980776243","https://openalex.org/W1997530783","https://openalex.org/W2105842272","https://openalex.org/W2114315281","https://openalex.org/W2137165876","https://openalex.org/W2150102617","https://openalex.org/W2162965868","https://openalex.org/W2166706824","https://openalex.org/W2170240176","https://openalex.org/W2251939518","https://openalex.org/W2493916176","https://openalex.org/W2558203065","https://openalex.org/W2563351168","https://openalex.org/W2574535369","https://openalex.org/W2606092111","https://openalex.org/W2606974598","https://openalex.org/W2759474451","https://openalex.org/W2782382326","https://openalex.org/W2788667846","https://openalex.org/W2798812533","https://openalex.org/W2896807716","https://openalex.org/W2905279751","https://openalex.org/W2951534261","https://openalex.org/W2962849707","https://openalex.org/W2962996600","https://openalex.org/W2963047186","https://openalex.org/W2963139477","https://openalex.org/W2971327572","https://openalex.org/W2996726036","https://openalex.org/W3022912079","https://openalex.org/W3034503922","https://openalex.org/W3091968381","https://openalex.org/W3114932121","https://openalex.org/W3177457472","https://openalex.org/W4239510810","https://openalex.org/W4298042201","https://openalex.org/W6677222910","https://openalex.org/W6696936656","https://openalex.org/W6718053083","https://openalex.org/W6763238093","https://openalex.org/W6784032422"],"related_works":["https://openalex.org/W2384888906","https://openalex.org/W2144190808","https://openalex.org/W2101955803","https://openalex.org/W2376314740","https://openalex.org/W2366644548","https://openalex.org/W2151447942","https://openalex.org/W2357241418","https://openalex.org/W2119214692","https://openalex.org/W2611614995","https://openalex.org/W2469626427"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5],"large":[6],"Chinese":[7,43,62],"news":[8,21,44,63],"article":[9,53],"dataset":[10,45],"with":[11,28,83],"4.4":[12],"million":[13],"articles.":[14],"These":[15],"articles":[16],"are":[17,26,89],"obtained":[18],"from":[19],"different":[20],"channels":[22],"and":[23,32,52,72,86],"sources.":[24],"They":[25],"labeled":[27],"multi-level":[29],"topic":[30,50,64],"categories,":[31],"some":[33],"of":[34,79],"them":[35],"also":[36,59,90],"have":[37],"summaries.":[38],"This":[39],"is":[40,58],"the":[41,60,68,80],"first":[42],"that":[46],"has":[47],"both":[48],"hierarchical":[49],"labels":[51],"full":[54],"texts.":[55],"And":[56],"it":[57],"largest":[61],"dataset.":[65],"We":[66],"describe":[67],"data":[69],"collection,":[70],"annotation":[71],"quality":[73],"evaluation":[74],"process.":[75],"The":[76],"basic":[77],"statistics":[78],"dataset,":[81],"comparison":[82],"other":[84],"datasets":[85],"benchmark":[87],"experiments":[88],"presented.":[91]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
