{"id":"https://openalex.org/W1597521498","doi":"https://doi.org/10.1109/percomw.2015.7134006","title":"Temporal reasoning on Twitter streams using semantic web technologies","display_name":"Temporal reasoning on Twitter streams using semantic web technologies","publication_year":2015,"publication_date":"2015-03-01","ids":{"openalex":"https://openalex.org/W1597521498","doi":"https://doi.org/10.1109/percomw.2015.7134006","mag":"1597521498"},"language":"en","primary_location":{"id":"doi:10.1109/percomw.2015.7134006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomw.2015.7134006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103141049","display_name":"Meng Cui","orcid":"https://orcid.org/0000-0003-2916-4618"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Meng Cui","raw_affiliation_strings":["Trinity College Dublin, School of Computer Science & Statistics, Dublin, Ireland","[School of Computer Science and Statistics, Trinity College Dublin,Dublin,Ireland]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Trinity College Dublin, School of Computer Science & Statistics, Dublin, Ireland","institution_ids":["https://openalex.org/I205274468"]},{"raw_affiliation_string":"[School of Computer Science and Statistics, Trinity College Dublin,Dublin,Ireland]","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102190090","display_name":"Wei Tai","orcid":null},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Wei Tai","raw_affiliation_strings":["Knowledge and Data Engineering Group, School of Computer Science & Statistics, Dublin, Ireland","Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Knowledge and Data Engineering Group, School of Computer Science & Statistics, Dublin, Ireland","institution_ids":[]},{"raw_affiliation_string":"Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020871962","display_name":"Declan O\u2019Sullivan","orcid":"https://orcid.org/0000-0003-1090-3548"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Declan O'Sullivan","raw_affiliation_strings":["University of Dublin Trinity College, Dublin, IE","Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Dublin Trinity College, Dublin, IE","institution_ids":["https://openalex.org/I205274468"]},{"raw_affiliation_string":"Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I205274468"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205274468"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05129879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"529","issue":null,"first_page":"129","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9994000196456909,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/data-stream-mining","display_name":"Data stream mining","score":0.8873680830001831},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8321914672851562},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.7413378357887268},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.6539319157600403},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.49334612488746643},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.480478435754776},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47633296251296997},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.46155214309692383},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4308536946773529},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38998475670814514},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.27560338377952576}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.8873680830001831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8321914672851562},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.7413378357887268},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.6539319157600403},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.49334612488746643},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.480478435754776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47633296251296997},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.46155214309692383},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4308536946773529},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38998475670814514},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27560338377952576},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/percomw.2015.7134006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomw.2015.7134006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320847","display_name":"Science Foundation Ireland","ror":"https://ror.org/0271asj38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W112415505","https://openalex.org/W155754185","https://openalex.org/W205072252","https://openalex.org/W1497870168","https://openalex.org/W1528610972","https://openalex.org/W1542433116","https://openalex.org/W1551505855","https://openalex.org/W1580256897","https://openalex.org/W1582258607","https://openalex.org/W1602744014","https://openalex.org/W1899971230","https://openalex.org/W1966302589","https://openalex.org/W1972793074","https://openalex.org/W1978947899","https://openalex.org/W1979822491","https://openalex.org/W2030790437","https://openalex.org/W2052845097","https://openalex.org/W2095692007","https://openalex.org/W2100515808","https://openalex.org/W2101906686","https://openalex.org/W2109360361","https://openalex.org/W2110262545","https://openalex.org/W2114314131","https://openalex.org/W2122540544","https://openalex.org/W2124499489","https://openalex.org/W2142738471","https://openalex.org/W2154829072","https://openalex.org/W2163040665","https://openalex.org/W2258864641","https://openalex.org/W2336273033","https://openalex.org/W2396067683","https://openalex.org/W3101974058","https://openalex.org/W6604581957","https://openalex.org/W6606274072","https://openalex.org/W6608275666","https://openalex.org/W6631638556","https://openalex.org/W6632956346","https://openalex.org/W6634528670","https://openalex.org/W6634928028","https://openalex.org/W6636221203","https://openalex.org/W6692211092","https://openalex.org/W6703402009","https://openalex.org/W6711709627"],"related_works":["https://openalex.org/W4288026155","https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W4361801939","https://openalex.org/W2802243998"],"abstract_inverted_index":{"There":[0,40],"has":[1,41,71],"been":[2,42,135],"a":[3,43,90,163],"significant":[4,59],"increase":[5,45],"in":[6,9,46,55,73,123],"recent":[7],"years":[8],"the":[10,26,83,119,140,143,152,154],"volume":[11],"and":[12,61,150],"diversity":[13],"of":[14,16,28,52,63,101,118,142,157],"streams":[15,19,23,54,100],"data,":[17,130],"data":[18,22,31,102,159,169],"from":[20,25],"sensors,":[21],"arising":[24],"analysis":[27,51,156],"content":[29],"or":[30,68],"mining,":[32],"right":[33],"through":[34],"to":[35,57,65,77,93,125,148],"user":[36],"generated":[37],"Twitter":[38,158],"streams.":[39,84,170],"corresponding":[44],"demand":[47],"for":[48,167],"more":[49,112],"real-time":[50,155],"these":[53],"order":[56,124,147],"spot":[58],"events":[60],"trends":[62],"interest":[64],"an":[66,74],"individual":[67],"business.":[69],"This":[70],"resulted":[72],"increased":[75],"need":[76],"achieve":[78],"efficient":[79],"temporal":[80,95],"reasoning":[81,96,144],"upon":[82],"In":[85,146],"this":[86],"paper,":[87],"we":[88,109],"present":[89],"novel":[91],"approach":[92],"perform":[94],"on":[97],"real":[98],"time":[99,120],"using":[103],"Semantic":[104],"Web":[105],"Technologies":[106],"so":[107],"that":[108],"could":[110],"derive":[111],"valuable":[113],"information":[114],"by":[115],"taking":[116],"account":[117],"dimension.":[121],"Moreover,":[122],"deal":[126],"with":[127],"such":[128,168],"high-frequency":[129],"several":[131],"filter":[132],"mechanisms":[133],"have":[134],"implemented":[136],"to,":[137],"significantly,":[138],"improve":[139],"performance":[141],"process.":[145],"illustrate":[149],"evaluate":[151],"approach,":[153],"is":[160],"taken":[161],"as":[162],"concrete":[164],"use":[165],"case":[166]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
