{"id":"https://openalex.org/W1983963795","doi":"https://doi.org/10.1145/1150402.1150456","title":"Event detection from evolution of click-through data","display_name":"Event detection from evolution of click-through data","publication_year":2006,"publication_date":"2006-08-20","ids":{"openalex":"https://openalex.org/W1983963795","doi":"https://doi.org/10.1145/1150402.1150456","mag":"1983963795"},"language":"en","primary_location":{"id":"doi:10.1145/1150402.1150456","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1150402.1150456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5075130969","display_name":"Qiankun Zhao","orcid":"https://orcid.org/0000-0001-7804-0430"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG","US"],"is_corresponding":true,"raw_author_name":"Qiankun Zhao","raw_affiliation_strings":["Pennsylvania State University &amp; Nanyang Technological University, Singapore","Pennsylvania State University & Nanyang Technological University, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University &amp; Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005","https://openalex.org/I130769515"]},{"raw_affiliation_string":"Pennsylvania State University & Nanyang Technological University, Singapore#TAB#","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101884287","display_name":"Tie\u2010Yan Liu","orcid":"https://orcid.org/0000-0002-0476-8020"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG","US"],"is_corresponding":false,"raw_author_name":"Tie-Yan Liu","raw_affiliation_strings":["Pennsylvania State University &amp; Nanyang Technological University, Singapore","Pennsylvania State University & Nanyang Technological University, Singapore#TAB#"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University &amp; Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005","https://openalex.org/I130769515"]},{"raw_affiliation_string":"Pennsylvania State University & Nanyang Technological University, Singapore#TAB#","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061002947","display_name":"Sourav S. Bhowmick","orcid":"https://orcid.org/0000-0003-1957-8016"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sourav S. Bhowmick","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103733614","display_name":"Wei\u2010Ying Ma","orcid":"https://orcid.org/0000-0002-7384-0735"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Ying Ma","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075130969"],"corresponding_institution_ids":["https://openalex.org/I130769515","https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":12.928,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.98128833,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"484","last_page":"493"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9994000196456909,"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/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.7700324058532715},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.542115330696106},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.46498507261276245},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46432700753211975},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.4528558552265167},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.426916241645813},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.38531821966171265},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3845868408679962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2181113362312317},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12419825792312622}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7700324058532715},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.542115330696106},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.46498507261276245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46432700753211975},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.4528558552265167},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.426916241645813},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.38531821966171265},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3845868408679962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2181113362312317},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12419825792312622}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1150402.1150456","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1150402.1150456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.495.7055","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.495.7055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cais.ntu.edu.sg/~assourav/papers/KDD-Event-06.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1483621318","https://openalex.org/W1972645849","https://openalex.org/W1973867972","https://openalex.org/W1998224037","https://openalex.org/W2046002391","https://openalex.org/W2047221353","https://openalex.org/W2052142057","https://openalex.org/W2055294489","https://openalex.org/W2072284402","https://openalex.org/W2111363262","https://openalex.org/W2117831564","https://openalex.org/W2121947440","https://openalex.org/W2129235726","https://openalex.org/W2133184712","https://openalex.org/W2135843591","https://openalex.org/W2143317703","https://openalex.org/W2165299010","https://openalex.org/W2481930235","https://openalex.org/W2799004609"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W2080136900","https://openalex.org/W2999799752","https://openalex.org/W2372768926","https://openalex.org/W2054458431","https://openalex.org/W2115167491","https://openalex.org/W3088754131","https://openalex.org/W3038848193"],"abstract_inverted_index":{"Previous":[0],"efforts":[1],"on":[2,11,108,187,202,232],"event":[3,52,66,166,247],"detection":[4,53,167],"from":[5,36,54,258],"the":[6,18,30,37,42,90,113,126,137,163,171,175,179,194,210,218,225,233,249,266],"web":[7,12,22,46,261],"have":[8,83],"focused":[9],"primarily":[10],"content":[13],"and":[14,64,128,133],"structure":[15],"data":[16,44,56,60,256],"ignoring":[17],"rich":[19],"collection":[20],"of":[21,45,104,115,165,173,178],"log":[23,43],"data.":[24],"In":[25,193,217],"this":[26],"paper,":[27],"we":[28,97],"propose":[29],"first":[31,98,195],"approach":[32,268],"to":[33,157,170,213,224,243],"detect":[34],"events":[35],"click-through":[38,55,91,255],"data,":[39,92],"which":[40,124],"is":[41,57,61,118,140,149,168,185,241],"search":[47,262],"engines.":[48],"The":[49,182],"intuition":[50],"behind":[51],"that":[58,75,153,206,238,265],"such":[59,205,237],"often":[62],"event-driven":[63],"each":[65,147,207,239],"can":[67],"be":[68,155],"represented":[69,119],"as":[70,120],"a":[71,102,121,150,188,214,245,259],"set":[72],"ofquery-page":[73],"pairs":[74,198,222],"are":[76,199,228],"not":[77],"only":[78],"semantically":[79],"similar":[80,84],"but":[81],"also":[82],"evolution":[85,234],"pattern":[86],"over":[87],"time.":[88],"Given":[89],"in":[93,209],"our":[94],"proposed":[95,267],"approach,":[96],"segment":[99],"it":[100],"into":[101,142],"sequence":[103,114],"bipartite":[105,116],"graphs":[106,117],"based":[107,186,201,231],"theuser-defined":[109],"time":[110],"granularity.":[111],"Next,":[112],"vector-based":[122,138,180],"graph,":[123,145],"records":[125],"semantic":[127],"evolutionary":[129],"relationships":[130],"between":[131],"queries":[132],"pages.":[134],"After":[135],"that,":[136],"graph":[139,177,190],"transformed":[141],"its":[143],"dual":[144,176],"where":[146],"node":[148],"query-page":[151,197,221],"pair":[152],"will":[154],"used":[156],"represent":[158,244],"real":[159,254],"world":[160],"events.":[161],"Then,":[162],"problem":[164,172],"equivalent":[169],"clustering":[174,183],"graph.":[181],"process":[184],"two-phase":[189],"cut":[191],"algorithm.":[192],"phase,":[196,220],"clustered":[200,230],"thesemantic-based":[203],"similarity":[204,236],"cluster":[208,240],"result":[211],"corresponds":[212],"specific":[215,246,250],"topic.":[216,251],"second":[219],"related":[223],"same":[226],"topic":[227],"further":[229],"pattern-based":[235],"expected":[242],"under":[248],"Experiments":[252],"with":[253],"collected":[257],"commercial":[260],"engine":[263],"show":[264],"produces":[269],"high":[270],"quality":[271],"results.":[272]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
