{"id":"https://openalex.org/W4411624578","doi":"https://doi.org/10.1145/3703323.3703334","title":"Efficient Depth-First Search Approach for Mining Frequent Chain Episodes","display_name":"Efficient Depth-First Search Approach for Mining Frequent Chain Episodes","publication_year":2024,"publication_date":"2024-12-18","ids":{"openalex":"https://openalex.org/W4411624578","doi":"https://doi.org/10.1145/3703323.3703334"},"language":"en","primary_location":{"id":"doi:10.1145/3703323.3703334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3703334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3703334","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3703334","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080151644","display_name":"Santhosh B. Gandreti","orcid":"https://orcid.org/0000-0003-1009-9254"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Santhosh B. Gandreti","raw_affiliation_strings":["Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118622685","display_name":"J. Chandan","orcid":null},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandan J.","raw_affiliation_strings":["Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110111037","display_name":"P. S. Sastry","orcid":null},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. S. Sastry","raw_affiliation_strings":["Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Indian Institute of Science, Bangalore, Karnataka, IN","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080151644"],"corresponding_institution_ids":["https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50194788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9940999746322632,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9861000180244446,"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/computer-science","display_name":"Computer science","score":0.604351282119751},{"id":"https://openalex.org/keywords/chain","display_name":"Chain (unit)","score":0.4340662956237793}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.604351282119751},{"id":"https://openalex.org/C199185054","wikidata":"https://www.wikidata.org/wiki/Q552299","display_name":"Chain (unit)","level":2,"score":0.4340662956237793},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3703323.3703334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3703334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3703334","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3703323.3703334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703323.3703334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3703323.3703334","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411624578.pdf","grobid_xml":"https://content.openalex.org/works/W4411624578.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W188289891","https://openalex.org/W1605031662","https://openalex.org/W2001456586","https://openalex.org/W2003957650","https://openalex.org/W2036514379","https://openalex.org/W2071242348","https://openalex.org/W2094138658","https://openalex.org/W2096126105","https://openalex.org/W2117145599","https://openalex.org/W2129063259","https://openalex.org/W2130296213","https://openalex.org/W2137502531","https://openalex.org/W2146334655","https://openalex.org/W2156026066","https://openalex.org/W2166069657","https://openalex.org/W2200183807","https://openalex.org/W2347162546","https://openalex.org/W2585438171","https://openalex.org/W2804147849","https://openalex.org/W2806559507","https://openalex.org/W2922053267","https://openalex.org/W2925090368","https://openalex.org/W4220945580","https://openalex.org/W4220945983","https://openalex.org/W4282945419","https://openalex.org/W4285308339","https://openalex.org/W4288598360","https://openalex.org/W4291125983","https://openalex.org/W4300005065","https://openalex.org/W4313492058","https://openalex.org/W4387643453","https://openalex.org/W4389895386","https://openalex.org/W4390548085","https://openalex.org/W4395475740"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Frequent":[0],"episode":[1],"mining":[2,55,109,132],"is":[3,16,70,81,142,154,182],"a":[4,19,42,71,126,165],"popular":[5],"method":[6],"of":[7,21,30,39,60,89,144],"finding":[8],"temporal":[9,43,48],"patterns":[10],"in":[11,50,103,158],"sequential":[12],"data.Here":[13],"the":[14,28,33,51,67,78,85,92,96,104,107,118,137,146,150,180,186],"data":[15],"viewed":[17],"as":[18,63],"sequence":[20],"events":[22],"characterized":[23],"by":[24],"an":[25],"event-type":[26],"and":[27,74,128,161],"time":[29],"occurrence,":[31],"and,":[32],"episodes":[34,46,61,65,76,83,90,114,134],"are":[35,53,84,115],"partially":[36],"ordered":[37],"sets":[38],"event-types,":[40],"representing":[41],"pattern.Frequently":[44],"occurring":[45],"capture":[47],"dependencies":[49],"data.There":[52],"efficient":[54,129,184],"algorithms":[56,110],"for":[57,112,131,170],"restricted":[58],"classes":[59],"such":[62],"serial":[64],"(where":[66,77],"partial":[68,79,97,166],"order":[69,80],"total":[72],"order)":[73,98],"parallel":[75],"null).Chain":[82],"most":[86],"general":[87],"form":[88],"(imposing":[91],"least":[93],"restrictions":[94],"on":[95,117,136],"that":[99,179],"have":[100],"been":[101],"considered":[102],"literature.At":[105],"present,":[106],"only":[108,157],"available":[111],"chain":[113,133],"based":[116,135],"Breadth-First-Search":[119],"(BFS)":[120],"approach.In":[121],"this":[122],"paper,":[123],"we":[124],"present":[125],"new":[127],"algorithm":[130,141,181],"Depth-First-Search":[138],"(DFS)":[139],"strategy.Our":[140],"capable":[143],"pruning":[145,171],"search":[147],"space":[148],"using":[149],"apriori":[151],"idea":[152],"(which":[153],"normally":[155],"used":[156],"BFS":[159,188],"methods)":[160],"it":[162],"also":[163],"includes":[164],"frequency":[167],"closure":[168],"check":[169],"some":[172],"redundant":[173],"frequent":[174],"episodes.We":[175],"show":[176],"through":[177],"simulations":[178],"more":[183],"than":[185],"existing":[187],"methods.":[189]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
