{"id":"https://openalex.org/W2084232642","doi":"https://doi.org/10.1145/1774088.1774319","title":"Mining temporal relationships among categories","display_name":"Mining temporal relationships among categories","publication_year":2010,"publication_date":"2010-03-22","ids":{"openalex":"https://openalex.org/W2084232642","doi":"https://doi.org/10.1145/1774088.1774319","mag":"2084232642"},"language":"en","primary_location":{"id":"doi:10.1145/1774088.1774319","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1774088.1774319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2010 ACM Symposium on Applied Computing","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/A5067779098","display_name":"Saket S. R. Mengle","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saket S. R. Mengle","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, Illinois"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, Illinois","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036610566","display_name":"Nazli Goharian","orcid":null},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nazli Goharian","raw_affiliation_strings":["Georgetown University, Washington, DC","Georgetown University , Washington, DC"],"affiliations":[{"raw_affiliation_string":"Georgetown University, Washington, DC","institution_ids":["https://openalex.org/I184565670"]},{"raw_affiliation_string":"Georgetown University , Washington, DC","institution_ids":["https://openalex.org/I184565670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067779098"],"corresponding_institution_ids":["https://openalex.org/I180949307"],"apc_list":null,"apc_paid":null,"fwci":1.3874,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.88346652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1107","last_page":"1108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9966999888420105,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9966999888420105,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9872000217437744,"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/T11269","display_name":"Algorithms and Data Compression","score":0.979200005531311,"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/timestamp","display_name":"Timestamp","score":0.8289534449577332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7059895396232605},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.6517274975776672},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.5811331868171692},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5664244890213013},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5313084125518799},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48692166805267334},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.48526355624198914},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3441814184188843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33778226375579834},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20464518666267395}],"concepts":[{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.8289534449577332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059895396232605},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.6517274975776672},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.5811331868171692},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5664244890213013},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5313084125518799},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48692166805267334},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.48526355624198914},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3441814184188843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33778226375579834},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20464518666267395},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1774088.1774319","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1774088.1774319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2010 ACM Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2033126752","https://openalex.org/W2040466507","https://openalex.org/W2115833276"],"related_works":["https://openalex.org/W2579899204","https://openalex.org/W2574209248","https://openalex.org/W2884490506","https://openalex.org/W2483088531","https://openalex.org/W4401920050","https://openalex.org/W2294686723","https://openalex.org/W2601871130","https://openalex.org/W2950359320","https://openalex.org/W4390493883","https://openalex.org/W2623500474"],"abstract_inverted_index":{"Temporal":[0],"text":[1,9],"mining":[2,73,97],"deals":[3],"with":[4,33,74],"discovering":[5],"temporal":[6],"patterns":[7],"in":[8,60],"over":[10],"a":[11],"period":[12],"of":[13],"time.":[14,36],"A":[15],"Theme":[16],"Evolution":[17,62],"Graph":[18,63],"(TEG)":[19],"is":[20,112],"used":[21],"to":[22,35],"visualize":[23],"when":[24],"new":[25],"themes":[26,44],"are":[27],"created":[28],"and":[29,57,70,88],"how":[30],"they":[31],"evolve":[32],"respect":[34],"TEG,":[37],"however,":[38],"does":[39],"not":[40],"represent":[41,58],"relationships":[42,56],"among":[43],"(or":[45],"categories)":[46],"that":[47,94],"share":[48],"same":[49],"timestamp.":[50],"We":[51,65],"focus":[52],"on":[53],"identifying":[54],"such":[55],"them":[59],"Relationship":[61],"(REG).":[64],"favorably":[66],"compare":[67],"passage":[68,109],"misclassification":[69,110],"association":[71,95],"rule":[72,96],"three":[75],"existing":[76,106],"approaches,":[77,107],"namely":[78],"KL":[79],"divergence":[80],"(KLD),":[81],"Consistent":[82],"bipartite":[83],"spectral":[84],"co-partitioning":[85],"graph":[86],"(CBSCG)":[87],"document":[89],"misclassification.":[90],"Our":[91],"evaluations":[92],"indicate":[93],"approach":[98,111],"statistically":[99],"significantly":[100],"(99%":[101],"confidence)":[102],"outperforms":[103],"the":[104,113],"other":[105],"while":[108],"second":[114],"most":[115],"effective":[116],"approach.":[117]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
