{"id":"https://openalex.org/W2739781989","doi":"https://doi.org/10.1145/3106237.3106291","title":"LAMP: data provenance for graph based machine learning algorithms through derivative computation","display_name":"LAMP: data provenance for graph based machine learning algorithms through derivative computation","publication_year":2017,"publication_date":"2017-08-02","ids":{"openalex":"https://openalex.org/W2739781989","doi":"https://doi.org/10.1145/3106237.3106291","mag":"2739781989"},"language":"en","primary_location":{"id":"doi:10.1145/3106237.3106291","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3106237.3106291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","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/A5101594068","display_name":"Shiqing Ma","orcid":"https://orcid.org/0000-0003-1551-8948"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shiqing Ma","raw_affiliation_strings":["Purdue University, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007570332","display_name":"Yousra Aafer","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yousra Aafer","raw_affiliation_strings":["Purdue University, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044027332","display_name":"Zhaogui Xu","orcid":"https://orcid.org/0009-0009-3975-2481"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaogui Xu","raw_affiliation_strings":["Nanjing University, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083644516","display_name":"Wen\u2010Chuan Lee","orcid":"https://orcid.org/0000-0001-9255-0170"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wen-Chuan Lee","raw_affiliation_strings":["Purdue University, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071575216","display_name":"Juan Zhai","orcid":"https://orcid.org/0000-0001-5017-8016"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Zhai","raw_affiliation_strings":["Nanjing University, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101952324","display_name":"Yingqi Liu","orcid":"https://orcid.org/0000-0003-1249-8929"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingqi Liu","raw_affiliation_strings":["Purdue University, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362465","display_name":"Xiangyu Zhang","orcid":"https://orcid.org/0000-0003-2138-4608"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangyu Zhang","raw_affiliation_strings":["Purdue University, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101594068"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":5.6912,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.96000803,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"786","last_page":"797"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.996399998664856,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9855999946594238,"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":0.7619898319244385},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6039532423019409},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5881755352020264},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5207253098487854},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4971340000629425},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.46682044863700867},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40325769782066345},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33940285444259644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3267107605934143},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2270791232585907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619898319244385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6039532423019409},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5881755352020264},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5207253098487854},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4971340000629425},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.46682044863700867},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40325769782066345},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33940285444259644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3267107605934143},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2270791232585907},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3106237.3106291","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3106237.3106291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.01RUT_INST:11695743410004646","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},{"id":"pmh:oai:alma.01RUT_INST:11695743410004646","is_oa":false,"landing_page_url":"https://scholarship.libraries.rutgers.edu/esploro/outputs/conferencePaper/LAMP-data-provenance-for-graph-based/991031794683304646","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4000000059604645,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W135267584","https://openalex.org/W624564079","https://openalex.org/W1525595230","https://openalex.org/W1551910050","https://openalex.org/W1563779243","https://openalex.org/W1585773866","https://openalex.org/W1717366851","https://openalex.org/W1764421085","https://openalex.org/W1854214752","https://openalex.org/W1990280147","https://openalex.org/W1993897382","https://openalex.org/W1994309501","https://openalex.org/W1995853580","https://openalex.org/W2005556331","https://openalex.org/W2007069447","https://openalex.org/W2007844788","https://openalex.org/W2020527870","https://openalex.org/W2022460880","https://openalex.org/W2030433745","https://openalex.org/W2031378219","https://openalex.org/W2041650849","https://openalex.org/W2056872955","https://openalex.org/W2057377421","https://openalex.org/W2068874164","https://openalex.org/W2090018148","https://openalex.org/W2093603746","https://openalex.org/W2095377587","https://openalex.org/W2098678088","https://openalex.org/W2098935637","https://openalex.org/W2108272874","https://openalex.org/W2117453981","https://openalex.org/W2117831564","https://openalex.org/W2131148034","https://openalex.org/W2131975293","https://openalex.org/W2167769381","https://openalex.org/W2219764230","https://openalex.org/W2232745072","https://openalex.org/W2260553848","https://openalex.org/W2294556882","https://openalex.org/W2301575454","https://openalex.org/W2316644690","https://openalex.org/W2384569204","https://openalex.org/W2549033012","https://openalex.org/W2755088640","https://openalex.org/W3185484028","https://openalex.org/W4206215385","https://openalex.org/W4240636081","https://openalex.org/W4365786623"],"related_works":["https://openalex.org/W2046435967","https://openalex.org/W4231775656","https://openalex.org/W2383646825","https://openalex.org/W2371018915","https://openalex.org/W2354191502","https://openalex.org/W1972225038","https://openalex.org/W3134658850","https://openalex.org/W2355938171","https://openalex.org/W2780079842","https://openalex.org/W2115091349"],"abstract_inverted_index":{"Data":[0],"provenance":[1,75,157],"tracking":[2,28],"determines":[3],"the":[4,35,89,99,104,109,171],"set":[5,57,141],"of":[6,37,58,63,66,91,142,173],"inputs":[7,59,127],"related":[8,38,128],"to":[9,43,52,114,117,129],"a":[10,55,74,140],"given":[11],"output.":[12],"It":[13],"enables":[14],"quality":[15],"control":[16,134],"and":[17,108,146,155],"problem":[18,176],"diagnosis":[19,177],"in":[20,47,175,178],"data":[21,106,147,179],"engineering.":[22,180],"Most":[23],"existing":[24],"techniques":[25],"work":[26],"by":[27,83,97],"program":[29,159],"dependencies.":[30],"They":[31],"cannot":[32],"quantitatively":[33],"assess":[34],"importance":[36,90,125],"inputs,":[39],"which":[40,48],"is":[41],"critical":[42],"machine":[44,79],"learning":[45,80],"algorithms,":[46],"an":[49,92,95],"output":[50,96],"tends":[51],"depend":[53],"on":[54,139],"huge":[56],"while":[60],"only":[61],"some":[62],"them":[64],"are":[65],"importance.":[67],"In":[68,120],"this":[69],"paper,":[70],"we":[71],"propose":[72],"LAMP,":[73],"computation":[76,113],"system":[77],"for":[78,94,126],"algorithms.":[81],"Inspired":[82],"automatic":[84],"differentiation":[85],"(AD),":[86],"LAMP":[87,102,151,174],"quantifies":[88],"input":[93],"computing":[98],"partial":[100],"derivative.":[101],"separates":[103],"original":[105],"processing":[107],"more":[110,153],"expensive":[111],"derivative":[112],"different":[115],"processes":[116],"achieve":[118],"cost-effectiveness.":[119],"addition,":[121],"it":[122],"allows":[123],"quantifying":[124],"discrete":[130],"behavior,":[131],"such":[132],"as":[133],"flow":[135],"selection.":[136],"The":[137],"evaluation":[138],"real":[143],"world":[144],"programs":[145],"sets":[148],"illustrates":[149],"that":[150],"produces":[152],"precise":[154],"succinct":[156],"than":[158],"dependence":[160],"based":[161],"techniques,":[162],"with":[163],"much":[164],"less":[165],"overhead.":[166],"Our":[167],"case":[168],"studies":[169],"demonstrate":[170],"potential":[172]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
