{"id":"https://openalex.org/W2907170049","doi":"https://doi.org/10.1109/icbk.2018.00026","title":"Snapshot Visualization of Complex Graphs with Force-Directed Algorithms","display_name":"Snapshot Visualization of Complex Graphs with Force-Directed Algorithms","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2907170049","doi":"https://doi.org/10.1109/icbk.2018.00026","mag":"2907170049"},"language":"en","primary_location":{"id":"doi:10.1109/icbk.2018.00026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbk.2018.00026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Knowledge (ICBK)","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/A5031869672","display_name":"Se-Hang Cheong","orcid":"https://orcid.org/0000-0002-3459-1385"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Se-Hang Cheong","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau dit"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau dit","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022730826","display_name":"Yain\u2010Whar Si","orcid":"https://orcid.org/0000-0001-8468-6182"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Yain-Whar Si","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau dit"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau dit","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":null,"apc_paid":null,"fwci":0.106,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49016811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"139","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10799","display_name":"Data Visualization and Analytics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9843000173568726,"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/T12720","display_name":"Multimedia Communication and Technology","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7438585758209229},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7247896194458008},{"id":"https://openalex.org/keywords/graph-drawing","display_name":"Graph drawing","score":0.6868077516555786},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6810638308525085},{"id":"https://openalex.org/keywords/snapshot","display_name":"Snapshot (computer storage)","score":0.6308241486549377},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5305595397949219},{"id":"https://openalex.org/keywords/graph-layout","display_name":"Graph Layout","score":0.49135318398475647},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22713854908943176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22460207343101501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7438585758209229},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7247896194458008},{"id":"https://openalex.org/C112953755","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph drawing","level":3,"score":0.6868077516555786},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6810638308525085},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.6308241486549377},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5305595397949219},{"id":"https://openalex.org/C2911174283","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph Layout","level":4,"score":0.49135318398475647},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22713854908943176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22460207343101501},{"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:10.1109/icbk.2018.00026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbk.2018.00026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Knowledge (ICBK)","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":22,"referenced_works":["https://openalex.org/W634834491","https://openalex.org/W1020953626","https://openalex.org/W1568669012","https://openalex.org/W1591086553","https://openalex.org/W1595997489","https://openalex.org/W1953427887","https://openalex.org/W2021053884","https://openalex.org/W2024672209","https://openalex.org/W2028695285","https://openalex.org/W2036946626","https://openalex.org/W2040317976","https://openalex.org/W2075220720","https://openalex.org/W2167482691","https://openalex.org/W2280871022","https://openalex.org/W2294125121","https://openalex.org/W2397851279","https://openalex.org/W3022981850","https://openalex.org/W3023524558","https://openalex.org/W6635245242","https://openalex.org/W6635526364","https://openalex.org/W6777060225","https://openalex.org/W7001748135"],"related_works":["https://openalex.org/W2346931493","https://openalex.org/W2031908202","https://openalex.org/W2766563406","https://openalex.org/W3160329999","https://openalex.org/W2026729066","https://openalex.org/W2010800245","https://openalex.org/W2903996962","https://openalex.org/W2895526338","https://openalex.org/W4312076339","https://openalex.org/W2003783600"],"abstract_inverted_index":{"Force-directed":[0],"algorithms":[1,10,47,97,121],"are":[2,11,48],"widely":[3],"used":[4],"for":[5,19,36,126,147,158],"visualizing":[6],"graphs.":[7,21,39],"However,":[8],"these":[9,46],"computationally":[12],"expensive":[13],"in":[14,50,98],"producing":[15],"good":[16],"quality":[17,24,74,90],"layouts":[18],"complex":[20,38],"The":[22,40],"layout":[23],"is":[25],"largely":[26],"influenced":[27],"by":[28],"execution":[29],"time":[30,131],"and":[31,77,105,119,138,160],"methods'":[32],"input":[33],"parameters":[34],"especially":[35],"large":[37,127,137],"snapshots":[41,92],"of":[42,59,75,80,91,100,102,109],"visualization":[43,76],"generated":[44,93],"from":[45,94],"useful":[49],"presenting":[51],"the":[52,73,78,89,106,130],"current":[53],"view":[54],"or":[55],"a":[56,70],"past":[57],"state":[58],"an":[60],"information":[61],"on":[62],"timeslices.":[63],"Therefore,":[64],"researchers":[65],"often":[66],"need":[67],"to":[68],"make":[69],"trade-off":[71],"between":[72],"selection":[79],"appropriate":[81],"force-directed":[82,96],"algorithms.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87],"evaluate":[88],"7":[95],"terms":[99],"number":[101],"edge":[103,110],"crossing":[104],"standard":[107],"deviations":[108],"length.":[111],"Our":[112],"experimental":[113],"results":[114],"showed":[115],"that":[116],"KK,":[117],"FA2":[118],"DH":[120],"cannot":[122],"produce":[123],"satisfactory":[124],"visualizations":[125,157],"graphs":[128,140,148,162],"within":[129],"limit.":[132],"KK-MS-DS":[133,164],"algorithm":[134,154],"can":[135],"process":[136],"planar":[139],"but":[141],"it":[142],"does":[143],"not":[144],"perform":[145],"well":[146],"with":[149],"low":[150],"average":[151],"degrees.":[152],"KK-MS":[153],"produces":[155],"better":[156],"sparse":[159],"non-clustered":[161],"than":[163],"algorithm.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
