{"id":"https://openalex.org/W3171387949","doi":"https://doi.org/10.1007/s10994-022-06156-1","title":"Meta-interpretive learning as metarule specialisation","display_name":"Meta-interpretive learning as metarule specialisation","publication_year":2022,"publication_date":"2022-04-15","ids":{"openalex":"https://openalex.org/W3171387949","doi":"https://doi.org/10.1007/s10994-022-06156-1","mag":"3171387949"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-022-06156-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06156-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06156-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06156-1.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024829092","display_name":"Stassa Patsantzis","orcid":"https://orcid.org/0000-0002-2266-4663"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"S. Patsantzis","raw_affiliation_strings":["Imperial College London, London, UK"],"raw_orcid":"https://orcid.org/0000-0002-2266-4663","affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076917665","display_name":"Stephen Muggleton","orcid":"https://orcid.org/0000-0001-6061-6104"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"S. H. Muggleton","raw_affiliation_strings":["Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024829092"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":{"value":3290,"currency":"USD","value_usd":3290},"apc_paid":{"value":3290,"currency":"USD","value_usd":3290},"fwci":0.3796,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65781193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"111","issue":"10","first_page":"3703","last_page":"3731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9958999752998352,"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/cardinality","display_name":"Cardinality (data modeling)","score":0.8380587100982666},{"id":"https://openalex.org/keywords/sort","display_name":"sort","score":0.6565004587173462},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6213400959968567},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.6205362677574158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6106765866279602},{"id":"https://openalex.org/keywords/datalog","display_name":"Datalog","score":0.5919040441513062},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5804414749145508},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47458764910697937},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4664691388607025},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4606153964996338},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4225860834121704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4098162353038788},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39170607924461365},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.33034610748291016},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3251316547393799},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.3071075677871704},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1402241289615631},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12060105800628662}],"concepts":[{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.8380587100982666},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.6565004587173462},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6213400959968567},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6205362677574158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6106765866279602},{"id":"https://openalex.org/C148230440","wikidata":"https://www.wikidata.org/wiki/Q1172264","display_name":"Datalog","level":2,"score":0.5919040441513062},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5804414749145508},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47458764910697937},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4664691388607025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4606153964996338},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4225860834121704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4098162353038788},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39170607924461365},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.33034610748291016},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3251316547393799},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3071075677871704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1402241289615631},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12060105800628662},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-022-06156-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06156-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06156-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-022-06156-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06156-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06156-1.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G1795072736","display_name":null,"funder_award_id":"EP/R022291/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3171387949.pdf","grobid_xml":"https://content.openalex.org/works/W3171387949.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W41262972","https://openalex.org/W198381195","https://openalex.org/W1514468887","https://openalex.org/W1769664091","https://openalex.org/W1946621657","https://openalex.org/W1987902506","https://openalex.org/W2076020349","https://openalex.org/W2091092523","https://openalex.org/W2100738443","https://openalex.org/W2112529578","https://openalex.org/W2167685423","https://openalex.org/W2169042011","https://openalex.org/W2212036697","https://openalex.org/W2397054552","https://openalex.org/W2403468034","https://openalex.org/W2520262084","https://openalex.org/W2520858206","https://openalex.org/W2574654054","https://openalex.org/W2798878581","https://openalex.org/W2888757411","https://openalex.org/W2899376621","https://openalex.org/W2914215741","https://openalex.org/W2918466505","https://openalex.org/W2962924847","https://openalex.org/W2965522163","https://openalex.org/W3004540582","https://openalex.org/W3119214637","https://openalex.org/W3127510592","https://openalex.org/W3130268038","https://openalex.org/W3177100526","https://openalex.org/W4255129615","https://openalex.org/W6601651175","https://openalex.org/W6607924690","https://openalex.org/W6636146035","https://openalex.org/W6688884716","https://openalex.org/W7027713560"],"related_works":["https://openalex.org/W2955734379","https://openalex.org/W2049216635","https://openalex.org/W3121709727","https://openalex.org/W1537382653","https://openalex.org/W2517279098","https://openalex.org/W2145813209","https://openalex.org/W2309621853","https://openalex.org/W2030105170","https://openalex.org/W2893316903","https://openalex.org/W1709921721"],"abstract_inverted_index":{"Abstract":[0],"In":[1,20],"Meta-interpretive":[2],"learning":[3],"(MIL)":[4],"the":[5,18,57,84,106,115,132,147,150,155,163],"metarules,":[6],"second-order":[7,26],"datalog":[8],"clauses":[9,144],"acting":[10],"as":[11,125,158,171],"inductive":[12],"bias,":[13],"are":[14,52,70,175,190],"manually":[15],"defined":[16],"by":[17,33,42,54,74,128,178,182],"user.":[19],"this":[21],"work":[22],"we":[23],"show":[24,47,104,169],"that":[25,48,66,105,170,194],"metarules":[27,41,51,60,69,79,140,174,180,197],"for":[28,89],"MIL":[29,124,133,164],"can":[30,198],"be":[31,101],"learned":[32,181],"MIL.":[34],"We":[35,103,122,130,153,192],"define":[36],"a":[37,62,109,160],"generality":[38],"ordering":[39],"of":[40,56,76,86,98,108,117,149,162],"$$\\theta$$":[43],"\u03b8":[44],"-subsumption":[45],"and":[46,65,88,145,187],"user-defined":[49,172,200],"sort":[50,173,179],"derivable":[53,73],"specialisation":[55,75,127,135],"most-general":[58],"matrix":[59,68],"in":[61,71,114,119],"language":[63,111],"class;":[64],"these":[67],"turn":[72],"third-order":[77],"punch":[78,120],"with":[80],"variables":[81],"quantified":[82],"over":[83],"set":[85],"atoms":[87],"which":[90],"only":[91],"an":[92],"upper":[93],"bound":[94],"on":[95],"their":[96],"number":[97,116],"literals":[99,118],"need":[100],"user-defined.":[102],"cardinality":[107],"metarule":[110,126,134],"is":[112],"polynomial":[113],"metarules.":[121,201],"re-frame":[123],"resolution.":[129],"modify":[131],"operator":[136,157],"to":[137],"return":[138],"new":[139,151,156],"rather":[141],"than":[142],"first-order":[143],"prove":[146],"correctness":[148],"operator.":[152],"implement":[154],"TOIL,":[159,183],"sub-system":[161],"system":[165],"Louise.":[166],"Our":[167],"experiments":[168],"progressively":[176],"replaced":[177],"Louise\u2019s":[184],"predictive":[185],"accuracy":[186],"training":[188],"times":[189],"maintained.":[191],"conclude":[193],"automatically":[195],"derived":[196],"replace":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}
