{"id":"https://openalex.org/W2914279424","doi":"https://doi.org/10.1109/bigdata.2018.8622638","title":"Relational Similarity Machines (RSM): A Similarity-based Learning Framework for Graphs","display_name":"Relational Similarity Machines (RSM): A Similarity-based Learning Framework for Graphs","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2914279424","doi":"https://doi.org/10.1109/bigdata.2018.8622638","mag":"2914279424"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622638","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5009957887","display_name":"Ryan A. Rossi","orcid":"https://orcid.org/0000-0001-9758-0635"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ryan A. Rossi","raw_affiliation_strings":["Adobe Research"],"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101721234","display_name":"Rong Zhou","orcid":"https://orcid.org/0000-0002-5825-1094"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rong Zhou","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059294839","display_name":"Nesreen K. Ahmed","orcid":"https://orcid.org/0000-0002-7913-4962"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nesreen K. Ahmed","raw_affiliation_strings":["Intel Labs"],"affiliations":[{"raw_affiliation_string":"Intel Labs","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038305381","display_name":"Hoda Eldardiry","orcid":"https://orcid.org/0000-0002-9712-6667"},"institutions":[{"id":"https://openalex.org/I173498003","display_name":"Palo Alto Research Center","ror":"https://ror.org/0529fxt39","country_code":"US","type":"facility","lineage":["https://openalex.org/I173498003","https://openalex.org/I4210132870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hoda Eldardiry","raw_affiliation_strings":["Palo Alto Research Center"],"affiliations":[{"raw_affiliation_string":"Palo Alto Research Center","institution_ids":["https://openalex.org/I173498003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009957887"],"corresponding_institution_ids":["https://openalex.org/I1306409833"],"apc_list":null,"apc_paid":null,"fwci":0.9772,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82690083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"3","issue":null,"first_page":"1807","last_page":"1816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9975000023841858,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9713000059127808,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/homophily","display_name":"Homophily","score":0.8502597808837891},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7232563495635986},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7211611270904541},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.6880399584770203},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.614126443862915},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5445132851600647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5259364247322083},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.5133894681930542},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.436059832572937},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3532085418701172},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32476741075515747},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17906057834625244}],"concepts":[{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.8502597808837891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232563495635986},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7211611270904541},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.6880399584770203},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.614126443862915},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5445132851600647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5259364247322083},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.5133894681930542},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.436059832572937},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3532085418701172},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32476741075515747},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17906057834625244},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622638","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W92973652","https://openalex.org/W298891370","https://openalex.org/W415688925","https://openalex.org/W1501299699","https://openalex.org/W1506965148","https://openalex.org/W1589355053","https://openalex.org/W1967947187","https://openalex.org/W1969968931","https://openalex.org/W1972748503","https://openalex.org/W1979426401","https://openalex.org/W1990334093","https://openalex.org/W2003238113","https://openalex.org/W2021648931","https://openalex.org/W2021969955","https://openalex.org/W2025394193","https://openalex.org/W2028137574","https://openalex.org/W2044459325","https://openalex.org/W2062988160","https://openalex.org/W2063066574","https://openalex.org/W2069790826","https://openalex.org/W2072128103","https://openalex.org/W2074932875","https://openalex.org/W2076063813","https://openalex.org/W2080417696","https://openalex.org/W2092900780","https://openalex.org/W2094145958","https://openalex.org/W2098468675","https://openalex.org/W2100045227","https://openalex.org/W2101705355","https://openalex.org/W2126185296","https://openalex.org/W2130354913","https://openalex.org/W2133075925","https://openalex.org/W2134757269","https://openalex.org/W2136997350","https://openalex.org/W2137253512","https://openalex.org/W2139823104","https://openalex.org/W2139905147","https://openalex.org/W2142202346","https://openalex.org/W2143387805","https://openalex.org/W2143570267","https://openalex.org/W2145262290","https://openalex.org/W2147572845","https://openalex.org/W2148534792","https://openalex.org/W2153959628","https://openalex.org/W2156094048","https://openalex.org/W2159156271","https://openalex.org/W2164349448","https://openalex.org/W2274716813","https://openalex.org/W2399708603","https://openalex.org/W2527276559","https://openalex.org/W2566642465","https://openalex.org/W2610037356","https://openalex.org/W2911738047","https://openalex.org/W2963316155","https://openalex.org/W3101290021","https://openalex.org/W3112180085","https://openalex.org/W4210997624","https://openalex.org/W4231109964","https://openalex.org/W4294553782","https://openalex.org/W6603669155","https://openalex.org/W6614453200","https://openalex.org/W6655903370","https://openalex.org/W6675204935","https://openalex.org/W6675257273","https://openalex.org/W6680278043","https://openalex.org/W6680434193","https://openalex.org/W6680929914","https://openalex.org/W6681363145","https://openalex.org/W6683068184","https://openalex.org/W6731048174","https://openalex.org/W6758327135","https://openalex.org/W7065437122"],"related_works":["https://openalex.org/W2902086760","https://openalex.org/W3181676408","https://openalex.org/W1549959306","https://openalex.org/W320292658","https://openalex.org/W2186138942","https://openalex.org/W2806326686","https://openalex.org/W2001007279","https://openalex.org/W2079674650","https://openalex.org/W2945061532","https://openalex.org/W2389834944"],"abstract_inverted_index":{"Relational":[0,69],"machine":[1],"learning":[2,25,66,91],"has":[3,43],"become":[4],"increasingly":[5],"important":[6],"due":[7],"to":[8,84],"the":[9,101,104],"recent":[10],"proliferation":[11],"and":[12,26,52,88],"ubiquity":[13],"of":[14,96,103],"network":[15],"data.":[16],"However,":[17],"existing":[18,41],"methods":[19],"are":[20],"not":[21],"designed":[22,83],"for":[23,73,90],"interactive":[24],"have":[27],"many":[28],"unrealistic":[29],"assumptions":[30],"that":[31],"greatly":[32],"limit":[33],"their":[34],"utility":[35],"in":[36],"practice.":[37],"For":[38],"instance,":[39],"most":[40],"work":[42],"focused":[44],"on":[45,92],"graphs":[46],"with":[47,75],"high":[48],"relational":[49,65,77],"autocorrelation":[50],"(homophily)":[51],"perform":[53],"poorly":[54],"otherwise.":[55],"To":[56],"overcome":[57],"these":[58],"limitations,":[59],"this":[60],"paper":[61],"presents":[62],"a":[63,93],"similarity-based":[64],"framework":[67,81],"called":[68],"Similarity":[70],"Machines":[71],"(RSM)":[72],"networks":[74],"arbitrary":[76],"autocorrelation.":[78],"The":[79,98],"RSM":[80,105],"is":[82],"be":[85],"fast,":[86],"accurate,":[87],"flexible":[89],"wide":[94],"variety":[95],"networks.":[97],"experiments":[99],"demonstrate":[100],"effectiveness":[102],"framework.":[106]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}