{"id":"https://openalex.org/W2999716521","doi":"https://doi.org/10.1109/access.2020.2967407","title":"A Novel Link Prediction Method for Opportunistic Networks Based on Random Walk and a Deep Belief Network","display_name":"A Novel Link Prediction Method for Opportunistic Networks Based on Random Walk and a Deep Belief Network","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2999716521","doi":"https://doi.org/10.1109/access.2020.2967407","mag":"2999716521"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2967407","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967407","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962072.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962072.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011681680","display_name":"Ziliang Liao","orcid":"https://orcid.org/0000-0002-3125-341X"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziliang Liao","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-3125-341X","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091555427","display_name":"Linlan Liu","orcid":"https://orcid.org/0000-0002-6021-097X"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlan Liu","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021205475","display_name":"Yubin Chen","orcid":"https://orcid.org/0000-0002-9912-7655"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Chen","raw_affiliation_strings":["School of Software, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.6207,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84334274,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"16236","last_page":"16247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976999759674072,"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/T11478","display_name":"Caching and Content Delivery","score":0.9927999973297119,"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":0.7352556586265564},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.7186194658279419},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.5514675974845886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5179345011711121},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4986305236816406},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4946417510509491},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.467998206615448},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.44466838240623474},{"id":"https://openalex.org/keywords/stochastic-matrix","display_name":"Stochastic matrix","score":0.4310721457004547},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.409190833568573},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3887794017791748},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34718990325927734},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3244703412055969},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27597424387931824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17294064164161682},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11821329593658447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7352556586265564},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.7186194658279419},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.5514675974845886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5179345011711121},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4986305236816406},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4946417510509491},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.467998206615448},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.44466838240623474},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.4310721457004547},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.409190833568573},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3887794017791748},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34718990325927734},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3244703412055969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27597424387931824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17294064164161682},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11821329593658447},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2967407","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967407","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962072.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7411a4d603a24b7a9f0b8d0917f2d6ad","is_oa":true,"landing_page_url":"https://doaj.org/article/7411a4d603a24b7a9f0b8d0917f2d6ad","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 16236-16247 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2967407","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967407","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962072.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G2287122053","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u4fe1\u5ff5\u7f51\u7684\u4fbf\u643a\u8bbe\u5907\u4ea4\u6362\u7f51\u7edc\u94fe\u8def\u9884\u6d4b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61762065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8609606721","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65e0\u7ebf\u4f20\u611f\u5668\u7f51\u7edc\u94fe\u8def\u8d28\u91cf\u8bc4\u4f30\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61962037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999716521.pdf","grobid_xml":"https://content.openalex.org/works/W2999716521.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1212607079","https://openalex.org/W1982877521","https://openalex.org/W2024516601","https://openalex.org/W2133299088","https://openalex.org/W2552713313","https://openalex.org/W2564701426","https://openalex.org/W2610963935","https://openalex.org/W2783673162","https://openalex.org/W2786905911","https://openalex.org/W2789728367","https://openalex.org/W2898512177","https://openalex.org/W2905394989","https://openalex.org/W2926753566","https://openalex.org/W2929002894","https://openalex.org/W2932721059","https://openalex.org/W2963241486","https://openalex.org/W2969227524","https://openalex.org/W2969986837","https://openalex.org/W2970485609","https://openalex.org/W2973813692","https://openalex.org/W2974394841","https://openalex.org/W2979363158","https://openalex.org/W2982416027","https://openalex.org/W2982593180","https://openalex.org/W2986709981","https://openalex.org/W3003151267","https://openalex.org/W3003421099","https://openalex.org/W6761296881"],"related_works":["https://openalex.org/W1597743604","https://openalex.org/W2906214541","https://openalex.org/W2513422012","https://openalex.org/W2038723108","https://openalex.org/W2897826427","https://openalex.org/W2133034788","https://openalex.org/W4367367217","https://openalex.org/W2792607040","https://openalex.org/W2086397253","https://openalex.org/W2033630974"],"abstract_inverted_index":{"Link":[0],"prediction":[1,43],"is":[2,50,95,111,169],"to":[3,24,102],"estimate":[4],"the":[5,25,63,82,89,99,121,125,131,138,151,166],"possibility":[6],"of":[7,27,92,127,130],"future":[8],"links":[9],"among":[10],"nodes":[11],"by":[12,97],"utilizing":[13],"known":[14],"information":[15],"such":[16,149],"as":[17,150],"network":[18,84,86,118],"topology":[19],"and":[20,34,55,68,140,162,172],"node":[21,32],"attributes.":[22],"According":[23],"characteristics":[26,123],"opportunistic":[28,47,83,132],"networks":[29,48],"(topological":[30],"time-variation,":[31],"mobility":[33],"intermittent":[35],"connections),":[36],"this":[37],"paper":[38],"proposes":[39],"a":[40,56,70,104,108,115],"novel":[41],"link":[42],"approach":[44],"(IRWR-DBN)":[45],"for":[46],"that":[49,145],"based":[51,113],"on":[52,114,137],"random":[53,74],"walk":[54,75],"deep":[57,116],"belief":[58,117],"network.":[59,133],"First,":[60],"we":[61,80],"reconstruct":[62],"Markov":[64],"probability":[65],"transition":[66],"matrix":[67,91],"define":[69],"similarity":[71,90],"index-":[72],"improved":[73],"with":[76,147],"restart":[77],"(IRWR).":[78],"Second,":[79],"divide":[81],"into":[85],"snapshots.":[87],"Then,":[88],"each":[93],"snapshot":[94],"calculated":[96],"using":[98],"IRWR":[100],"index":[101,153],"construct":[103],"sample":[105],"set.":[106],"Finally,":[107],"predictive":[109],"model":[110],"constructed":[112],"which":[119],"extracts":[120],"time-domain":[122],"in":[124],"process":[126],"dynamic":[128],"evolution":[129],"The":[134],"experimental":[135],"results":[136],"ITC":[139],"MIT":[141],"Reality":[142],"datasets":[143],"show":[144],"compared":[146],"methods,":[148],"similarity-based":[152],"(CN,":[154],"AA,":[155],"Katz,":[156],"RA,":[157],"RWR),":[158],"convolutional":[159],"neural":[160,164],"network,":[161,165],"recurrent":[163],"proposed":[167],"method":[168],"more":[170],"accurate":[171],"stable.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}