{"id":"https://openalex.org/W2735518897","doi":"https://doi.org/10.1109/ijcnn.2017.7966076","title":"Deep learning approach to link weight prediction","display_name":"Deep learning approach to link weight prediction","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735518897","doi":"https://doi.org/10.1109/ijcnn.2017.7966076","mag":"2735518897"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","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/A5008832177","display_name":"Yuchen Hou","orcid":"https://orcid.org/0009-0009-7537-7500"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuchen Hou","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044712355","display_name":"Lawrence B. Holder","orcid":"https://orcid.org/0000-0002-6586-3144"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence B. Holder","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA","institution_ids":["https://openalex.org/I72951846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I72951846"],"apc_list":null,"apc_paid":null,"fwci":0.5537,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.69114355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1855","last_page":"1862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.98089998960495,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.98089998960495,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9678999781608582,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9599999785423279,"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/link","display_name":"Link (geometry)","score":0.6910945773124695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6025294065475464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5327344536781311},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4899846613407135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4200628399848938},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1163114607334137}],"concepts":[{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.6910945773124695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025294065475464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5327344536781311},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4899846613407135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4200628399848938},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1163114607334137}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1614298861","https://openalex.org/W1686810756","https://openalex.org/W1922655562","https://openalex.org/W1970781863","https://openalex.org/W2052104835","https://openalex.org/W2102907934","https://openalex.org/W2112447569","https://openalex.org/W2116341502","https://openalex.org/W2146530408","https://openalex.org/W2150607630","https://openalex.org/W2153579005","https://openalex.org/W2154454189","https://openalex.org/W2154851992","https://openalex.org/W2159697746","https://openalex.org/W2257646213","https://openalex.org/W2271840356","https://openalex.org/W2400801499","https://openalex.org/W2768375068","https://openalex.org/W2914484425","https://openalex.org/W2919115771","https://openalex.org/W2950577311","https://openalex.org/W2962756421","https://openalex.org/W2964341035","https://openalex.org/W3098818882","https://openalex.org/W3101685104","https://openalex.org/W3104097132","https://openalex.org/W3124468770","https://openalex.org/W4232932184","https://openalex.org/W4255949318","https://openalex.org/W4294170691","https://openalex.org/W4297571622","https://openalex.org/W6629815555","https://openalex.org/W6676727762","https://openalex.org/W6682691769","https://openalex.org/W6785740601"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Deep":[0],"learning":[1,46,96],"has":[2],"been":[3],"successful":[4],"in":[5,23,28,118],"various":[6],"domains":[7],"including":[8],"image":[9],"recognition,":[10],"speech":[11],"recognition":[12],"and":[13,63,81,88,105,111],"natural":[14],"language":[15],"processing.":[16],"However,":[17],"the":[18,74],"research":[19],"on":[20],"its":[21,89,112],"application":[22],"graph":[24,134],"mining":[25,135],"is":[26],"still":[27],"an":[29],"early":[30],"stage.":[31],"Here":[32],"we":[33],"present":[34],"Model":[35,77,91],"R,":[36],"a":[37,44],"neural":[38],"network":[39],"model":[40,54,87,110],"created":[41],"to":[42,48,67,101,116,128,132],"provide":[43,129],"deep":[45,95],"approach":[47,127],"link":[49,102],"weight":[50,103],"prediction":[51,104,121],"problem.":[52],"This":[53],"extracts":[55],"knowledge":[56,66],"of":[57,76,120],"nodes":[58],"from":[59],"known":[60],"links'":[61,70],"weights":[62],"uses":[64],"this":[65,125],"predict":[68],"unknown":[69],"weights.":[71],"We":[72,123],"demonstrate":[73],"power":[75],"R":[78,92],"through":[79],"experiments":[80],"compare":[82],"it":[83,106],"with":[84],"stochastic":[85,108],"block":[86,109],"derivatives.":[90],"shows":[93],"that":[94],"can":[97],"be":[98],"successfully":[99],"applied":[100],"outperforms":[107],"derivatives":[113],"by":[114],"up":[115],"73%":[117],"terms":[119],"accuracy.":[122],"anticipate":[124],"new":[126],"effective":[130],"solutions":[131],"more":[133],"tasks.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
