{"id":"https://openalex.org/W2015930231","doi":"https://doi.org/10.4304/jnw.9.01.216-222","title":"Global Trust Value Grading Calculation Method in P2P Network","display_name":"Global Trust Value Grading Calculation Method in P2P Network","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2015930231","doi":"https://doi.org/10.4304/jnw.9.01.216-222","mag":"2015930231"},"language":"en","primary_location":{"id":"doi:10.4304/jnw.9.01.216-222","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.9.01.216-222","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-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/A5044468616","display_name":"Min Liu","orcid":"https://orcid.org/0000-0001-6260-0480"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Min Liu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100768946","display_name":"Ying Li","orcid":"https://orcid.org/0000-0002-8252-067X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044468616"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08028619,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9503999948501587,"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":0.9165362119674683},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.5883321166038513},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.431391179561615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17096465826034546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9165362119674683},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.5883321166038513},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.431391179561615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17096465826034546},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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":1,"locations":[{"id":"doi:10.4304/jnw.9.01.216-222","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.9.01.216-222","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1544576535","https://openalex.org/W1983458885","https://openalex.org/W2003563417","https://openalex.org/W2022737986","https://openalex.org/W2023294530","https://openalex.org/W2029320105","https://openalex.org/W2069241392","https://openalex.org/W2086984950","https://openalex.org/W2096040597","https://openalex.org/W2098454198","https://openalex.org/W2099820907","https://openalex.org/W2102351287","https://openalex.org/W2103158338","https://openalex.org/W2105591650","https://openalex.org/W2115972678","https://openalex.org/W2128491622","https://openalex.org/W2135306594","https://openalex.org/W2136541117","https://openalex.org/W2141793797","https://openalex.org/W2142892896","https://openalex.org/W2400460575","https://openalex.org/W2506307255","https://openalex.org/W3140116328","https://openalex.org/W6632694843","https://openalex.org/W6657890986","https://openalex.org/W6983717111"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2064165679","https://openalex.org/W2358668433","https://openalex.org/W1588461101","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3208525924","https://openalex.org/W2885058781"],"abstract_inverted_index":{"The":[0],"paper":[1],"has":[2,29,106],"proposed":[3],"that":[4],"the":[5,60,65,83,86,101,104,110,119],"global":[6],"situation":[7,75],"trust":[8,17,76],"value":[9,77],"doesn\u2019t":[10],"depend":[11],"on":[12],"any":[13],"set":[14],"of":[15,24,50,59,78,85,112],"high":[16],"nodes":[18],"in":[19,68,70],"a":[20,41,48,71],"P2P":[21],"network":[22,43,57],"environment":[23],"grading":[25],"calculating":[26],"model.":[27],"It":[28],"given":[30],"its":[31],"distributed":[32],"implementation.":[33],"This":[34],"model":[35,105],"introduces":[36],"subtraction":[37],"clustering":[38],"method":[39],"to":[40],"large-scale":[42],"is":[44,81],"logically":[45],"divided":[46],"into":[47],"number":[49],"small":[51],"networks,":[52],"and":[53,62,94,114,117],"re-organized":[54],"as":[55],"overlay":[56],"structure":[58],"upper":[61],"lower":[63],"levels,":[64],"iterative":[66,120],"algorithms":[67],"parallel":[69],"small-scale":[72],"network.":[73],"Global":[74],"each":[79],"node":[80],"obtained,":[82],"convergence":[84],"iteration":[87],"level":[88],"synthesis":[89],"iterations":[90],"results.":[91],"Theoretical":[92],"analysis":[93],"simulation":[95],"results":[96],"show":[97],"that,":[98],"compared":[99],"with":[100],"existing":[102],"model,":[103],"improved":[107],"greatly":[108],"reduce":[109],"amount":[111],"computation":[113],"communication":[115],"overhead,":[116],"accelerate":[118],"convergence.":[121]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
