{"id":"https://openalex.org/W2909785353","doi":"https://doi.org/10.1145/3297001.3297053","title":"Applications of Machine Learning in Analysis of Citation Network","display_name":"Applications of Machine Learning in Analysis of Citation Network","publication_year":2019,"publication_date":"2019-01-03","ids":{"openalex":"https://openalex.org/W2909785353","doi":"https://doi.org/10.1145/3297001.3297053","mag":"2909785353"},"language":"en","primary_location":{"id":"doi:10.1145/3297001.3297053","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297001.3297053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM India Joint International Conference on Data Science and Management of Data","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/A5046388949","display_name":"Dinesh K. Pradhan","orcid":"https://orcid.org/0000-0001-9132-9255"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh K. Pradhan","raw_affiliation_strings":["Dept. of Computer Science & Engg., NIT Durgapur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engg., NIT Durgapur, India","institution_ids":["https://openalex.org/I155837530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042034956","display_name":"Joyita Chakraborty","orcid":"https://orcid.org/0009-0008-8294-7957"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Joyita Chakraborty","raw_affiliation_strings":["Dept. of Computer Science & Engg., NIT Durgapur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engg., NIT Durgapur, India","institution_ids":["https://openalex.org/I155837530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101813549","display_name":"Subrata Nandi","orcid":"https://orcid.org/0000-0002-8743-4770"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subrata Nandi","raw_affiliation_strings":["Dept. of Computer Science & Engg., NIT Durgapur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Engg., NIT Durgapur, India","institution_ids":["https://openalex.org/I155837530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155837530"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"330","last_page":"333"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T10102","display_name":"scientometrics and bibliometrics research","score":0.9588000178337097,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9585000276565552,"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/computer-science","display_name":"Computer science","score":0.7708770036697388},{"id":"https://openalex.org/keywords/citation","display_name":"Citation","score":0.7661795616149902},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5291058421134949},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5115419626235962},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5096113681793213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5042921304702759},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4914306402206421},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4749869406223297},{"id":"https://openalex.org/keywords/citation-analysis","display_name":"Citation analysis","score":0.4504035413265228},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44584643840789795},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4138895869255066},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20767396688461304},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09530478715896606},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08556172251701355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7708770036697388},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.7661795616149902},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5291058421134949},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5115419626235962},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5096113681793213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5042921304702759},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4914306402206421},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4749869406223297},{"id":"https://openalex.org/C105345328","wikidata":"https://www.wikidata.org/wiki/Q206276","display_name":"Citation analysis","level":3,"score":0.4504035413265228},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44584643840789795},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4138895869255066},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20767396688461304},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09530478715896606},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08556172251701355},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3297001.3297053","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297001.3297053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM India Joint International Conference on Data Science and Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1651321255","https://openalex.org/W2071167245","https://openalex.org/W2101900104","https://openalex.org/W2124689612","https://openalex.org/W2135673975","https://openalex.org/W2336463934","https://openalex.org/W2342176091","https://openalex.org/W2566366613","https://openalex.org/W2765353678","https://openalex.org/W2883840843"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W3183283580","https://openalex.org/W2337929971","https://openalex.org/W4313069709","https://openalex.org/W4283741549","https://openalex.org/W4250175685","https://openalex.org/W2360069064","https://openalex.org/W2052409349","https://openalex.org/W4281559401","https://openalex.org/W2951517996"],"abstract_inverted_index":{"Research":[0],"standard":[1],"and":[2,19,26,83,87,97,136,159],"quality":[3],"should":[4],"be":[5,45],"continuously":[6],"monitored":[7],"to":[8,44,59,115,147],"direct":[9],"progress":[10],"of":[11,38,53,72,80,89,108,122,133,139,142,156],"science":[12],"in":[13,22,34,74,150],"right":[14],"direction.":[15],"With":[16],"exponential":[17],"growth":[18],"continuous":[20],"expansion":[21],"citation":[23,75,101,120,134,143],"network,":[24,76],"manual":[25],"static":[27,148],"analysis":[28,68,107],"is":[29],"becoming":[30],"insignificant.":[31],"To":[32],"fill":[33],"the":[35,54,117],"gap,":[36],"application":[37],"machine":[39,62],"learning":[40],"models":[41],"might":[42],"prove":[43],"useful.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,57,113,128,153],"propose":[51],"some":[52],"problems":[55],"that":[56],"intend":[58],"solve":[60],"using":[61],"learning.":[63],"Among":[64],"various":[65],"applications":[66],"outlier":[67],"for":[69],"early":[70],"detection":[71],"anomalies":[73],"long":[77],"term":[78],"prediction":[79],"high":[81],"impact":[82],"seminal":[84],"authors,":[85],"papers":[86],"field":[88],"study,":[90],"deriving":[91],"inherent":[92],"features":[93],"on":[94],"diverse":[95,140],"temporal":[96],"demographic":[98],"scale":[99],"governing":[100],"structure":[102,121],"etc.":[103],"Starting":[104],"with":[105],"empirical":[106],"open":[109],"academic":[110],"graph":[111],"dataset,":[112],"try":[114],"understand":[116],"complex":[118],"relational":[119],"entities.":[123],"As":[124],"a":[125],"preliminary":[126],"step,":[127],"do":[129],"time":[130],"series":[131],"clustering":[132],"data":[135],"study":[137,158],"characteristics":[138],"profiles":[141],"curves.":[144],"When":[145],"compared":[146],"classification":[149],"past":[151,157],"literature,":[152],"overcome":[154],"drawbacks":[155],"get":[160],"better":[161],"insights.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}