{"id":"https://openalex.org/W2028544407","doi":"https://doi.org/10.1145/2484028.2484045","title":"Sumblr","display_name":"Sumblr","publication_year":2013,"publication_date":"2013-07-28","ids":{"openalex":"https://openalex.org/W2028544407","doi":"https://doi.org/10.1145/2484028.2484045","mag":"2028544407"},"language":"en","primary_location":{"id":"doi:10.1145/2484028.2484045","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2484028.2484045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","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/A5103017455","display_name":"Lidan Shou","orcid":"https://orcid.org/0000-0001-8062-8356"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lidan Shou","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","Zhejiang university, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang university, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744155","display_name":"Zhenhua Wang","orcid":"https://orcid.org/0000-0001-6388-7938"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Wang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","Zhejiang university, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang university, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451997","display_name":"Ke Chen","orcid":"https://orcid.org/0000-0002-3062-0900"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","Zhejiang university, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang university, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100389286","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-7483-0045"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","Zhejiang university, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang university, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103017455"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":14.6835,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.99349889,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"533","last_page":"542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9986000061035156,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.9370867013931274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8612473011016846},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.6998382806777954},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6535077095031738},{"id":"https://openalex.org/keywords/timeline","display_name":"Timeline","score":0.5651566982269287},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5304293632507324},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5300378799438477},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5056357383728027},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.486580491065979},{"id":"https://openalex.org/keywords/haystack","display_name":"Haystack","score":0.4599558115005493},{"id":"https://openalex.org/keywords/web-crawler","display_name":"Web crawler","score":0.4468650221824646},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4450471103191376},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43269652128219604},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3097866475582123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20795437693595886}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9370867013931274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8612473011016846},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.6998382806777954},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6535077095031738},{"id":"https://openalex.org/C4438859","wikidata":"https://www.wikidata.org/wiki/Q186117","display_name":"Timeline","level":2,"score":0.5651566982269287},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5304293632507324},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5300378799438477},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5056357383728027},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.486580491065979},{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.4599558115005493},{"id":"https://openalex.org/C13743948","wikidata":"https://www.wikidata.org/wiki/Q45842","display_name":"Web crawler","level":2,"score":0.4468650221824646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4450471103191376},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43269652128219604},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3097866475582123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20795437693595886},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2484028.2484045","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2484028.2484045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W192460397","https://openalex.org/W1509894598","https://openalex.org/W1512874001","https://openalex.org/W1517583229","https://openalex.org/W1573514622","https://openalex.org/W1884372994","https://openalex.org/W1901464671","https://openalex.org/W1967082914","https://openalex.org/W1977884995","https://openalex.org/W1980595271","https://openalex.org/W2007267444","https://openalex.org/W2011269336","https://openalex.org/W2014615172","https://openalex.org/W2036216970","https://openalex.org/W2076538837","https://openalex.org/W2083305840","https://openalex.org/W2083778364","https://openalex.org/W2089085556","https://openalex.org/W2089391273","https://openalex.org/W2095897464","https://openalex.org/W2099064293","https://openalex.org/W2128721751","https://openalex.org/W2148374900","https://openalex.org/W2149510050","https://openalex.org/W2150824314","https://openalex.org/W2154652894","https://openalex.org/W2166322082","https://openalex.org/W2170936641","https://openalex.org/W2184986707","https://openalex.org/W2535726973","https://openalex.org/W3101913037","https://openalex.org/W3138773240","https://openalex.org/W6630634684","https://openalex.org/W6634065907","https://openalex.org/W6682631176","https://openalex.org/W6684175902"],"related_works":["https://openalex.org/W4253878822","https://openalex.org/W1965563707","https://openalex.org/W4210692028","https://openalex.org/W1736550718","https://openalex.org/W2808729870","https://openalex.org/W2479343091","https://openalex.org/W2278064783","https://openalex.org/W3174858427","https://openalex.org/W2888780092","https://openalex.org/W2089702591"],"abstract_inverted_index":{"With":[0],"the":[1,174],"explosive":[2],"growth":[3],"of":[4,48,142,178],"microblogging":[5],"services,":[6],"short-text":[7],"messages":[8],"(also":[9],"known":[10],"as":[11,64],"tweets)":[12],"are":[13],"being":[14],"created":[15],"and":[16,37,54,79,90,120,139,157,176],"shared":[17],"at":[18],"an":[19,111],"unprecedented":[20],"rate.":[21],"Tweets":[22],"in":[23],"its":[24],"raw":[25],"form":[26],"can":[27],"be":[28],"incredibly":[29],"informative,":[30],"but":[31],"also":[32],"overwhelming.":[33],"For":[34],"both":[35],"end-users":[36],"data":[38],"analysts":[39],"it":[40],"is":[41],"a":[42,65,96,131,149],"nightmare":[43],"to":[44,67,84,117,160],"plow":[45],"through":[46],"millions":[47],"tweets":[49,119,172],"which":[50,154],"contain":[51],"enormous":[52],"noises":[53],"redundancies.":[55],"In":[56],"this":[57,69],"paper,":[58],"we":[59,82,129,147],"study":[60],"continuous":[61],"tweet":[62,92,106,113,165],"summarization":[63,74,133],"solution":[66],"address":[68],"problem.":[70],"While":[71],"traditional":[72],"document":[73],"methods":[75],"focus":[76],"on":[77,169],"static":[78],"small-scale":[80],"data,":[81],"aim":[83],"deal":[85],"with":[86],"dynamic,":[87],"quickly":[88],"arriving,":[89],"large-scale":[91,170],"streams.":[93,107,166],"We":[94,108],"propose":[95,110],"novel":[97],"prototype":[98],"called":[99,124],"Sumblr":[100],"(SUMmarization":[101],"By":[102],"stream":[103,114],"cLusteRing)":[104],"for":[105,135],"first":[109],"online":[112,137,156],"clustering":[115],"algorithm":[116],"cluster":[118],"maintain":[121],"distilled":[122],"statistics":[123],"Tweet":[125],"Cluster":[126],"Vectors.":[127],"Then":[128],"develop":[130],"TCV-Rank":[132],"technique":[134],"generating":[136],"summaries":[138,141,159],"historical":[140,158],"arbitrary":[143],"time":[144],"durations.":[145],"Finally,":[146],"describe":[148],"topic":[150],"evolvement":[151],"detection":[152],"method,":[153],"consumes":[155],"produce":[161],"timelines":[162],"automatically":[163],"from":[164],"Our":[167],"experiments":[168],"real":[171],"demonstrate":[173],"efficiency":[175],"effectiveness":[177],"our":[179],"approach.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":19},{"year":2016,"cited_by_count":18},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}