{"id":"https://openalex.org/W3023501492","doi":"https://doi.org/10.1137/19m1265971","title":"Compressive Sensing for Cut Improvement and Local Clustering","display_name":"Compressive Sensing for Cut Improvement and Local Clustering","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3023501492","doi":"https://doi.org/10.1137/19m1265971","mag":"3023501492"},"language":"en","primary_location":{"id":"doi:10.1137/19m1265971","is_oa":true,"landing_page_url":"https://doi.org/10.1137/19m1265971","pdf_url":"https://epubs.siam.org/doi/pdf/10.1137/19M1265971","source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://epubs.siam.org/doi/pdf/10.1137/19M1265971","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057710396","display_name":"Ming\u2010Jun Lai","orcid":"https://orcid.org/0000-0003-0274-2545"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ming-Jun Lai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063906541","display_name":"Daniel McKenzie","orcid":"https://orcid.org/0000-0001-5818-4867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Mckenzie","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057710396"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3521,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52889437,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2","issue":"2","first_page":"368","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9803000092506409,"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/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8637551069259644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5575239658355713},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4841383397579193},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.47723034024238586},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37867942452430725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.333614319562912},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.16249743103981018},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.056989818811416626}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8637551069259644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5575239658355713},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4841383397579193},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.47723034024238586},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37867942452430725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.333614319562912},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.16249743103981018},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.056989818811416626}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/19m1265971","is_oa":true,"landing_page_url":"https://doi.org/10.1137/19m1265971","pdf_url":"https://epubs.siam.org/doi/pdf/10.1137/19M1265971","source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1137/19m1265971","is_oa":true,"landing_page_url":"https://doi.org/10.1137/19m1265971","pdf_url":"https://epubs.siam.org/doi/pdf/10.1137/19M1265971","source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.550000011920929,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3395425912","display_name":null,"funder_award_id":"DMS 1521537","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3023501492.pdf","grobid_xml":"https://content.openalex.org/works/W3023501492.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W626380189","https://openalex.org/W1536930209","https://openalex.org/W1966119405","https://openalex.org/W1971421925","https://openalex.org/W1980921095","https://openalex.org/W2032336879","https://openalex.org/W2032961882","https://openalex.org/W2045078975","https://openalex.org/W2045107949","https://openalex.org/W2059658171","https://openalex.org/W2084309732","https://openalex.org/W2088759008","https://openalex.org/W2102907934","https://openalex.org/W2112173569","https://openalex.org/W2121947440","https://openalex.org/W2122799790","https://openalex.org/W2132914434","https://openalex.org/W2133576408","https://openalex.org/W2135512436","https://openalex.org/W2145096794","https://openalex.org/W2150256170","https://openalex.org/W2152322845","https://openalex.org/W2156377127","https://openalex.org/W2160979406","https://openalex.org/W2162148078","https://openalex.org/W2165874743","https://openalex.org/W2171878761","https://openalex.org/W2289917018","https://openalex.org/W2296616510","https://openalex.org/W2336317531","https://openalex.org/W2401137510","https://openalex.org/W2497095904","https://openalex.org/W2552069707","https://openalex.org/W2605215001","https://openalex.org/W2717496991","https://openalex.org/W2749605325","https://openalex.org/W2766962042","https://openalex.org/W2783779423","https://openalex.org/W2900745741","https://openalex.org/W2902567703","https://openalex.org/W2949667996","https://openalex.org/W2952057408","https://openalex.org/W2962801026","https://openalex.org/W2974040400","https://openalex.org/W3099741431","https://openalex.org/W3101676988","https://openalex.org/W4241998900","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4388258507","https://openalex.org/W2392013855","https://openalex.org/W4318064328","https://openalex.org/W2357926602","https://openalex.org/W2374569605","https://openalex.org/W2386062718","https://openalex.org/W899618282","https://openalex.org/W2386129765","https://openalex.org/W2368742525"],"abstract_inverted_index":{"Related":[0],"DatabasesWeb":[1],"of":[2],"Science":[3],"You":[4],"must":[5],"be":[6],"logged":[7],"in":[8],"with":[9],"an":[10],"active":[11],"subscription":[12],"to":[13],"view":[14],"this.Article":[15],"DataHistorySubmitted:":[16],"4":[17],"June":[18],"2019Accepted:":[19],"18":[20],"February":[21],"2020Published":[22],"online:":[23],"05":[24],"May":[25],"2020Keywordscluster":[26],"extraction,":[27],"local":[28],"clustering,":[29,33],"cut":[30],"improvement,":[31],"semisupervised":[32],"community":[34],"detection,":[35],"compressive":[36],"sensing,":[37],"sparse":[38],"solution,":[39],"graph":[40],"LaplacianAMS":[41],"Subject":[42],"Headings68Q25,":[43],"68R10,":[44],"68U05,":[45],"94A12Publication":[46],"DataISSN":[47],"(online):":[48],"2577-0187Publisher:":[49],"Society":[50],"for":[51],"Industrial":[52],"and":[53],"Applied":[54],"MathematicsCODEN:":[55],"sjmdaq":[56]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
