{"id":"https://openalex.org/W2603390332","doi":null,"title":"The role of feature construction in inductive rule learning","display_name":"The role of feature construction in inductive rule learning","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W2603390332","mag":"2603390332"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.4954","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.4954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bris.ac.uk/Publications/Papers/1000486.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5057936560","display_name":"Peter A. Flach","orcid":"https://orcid.org/0000-0001-6857-5810","observed_orcids":["https://orcid.org/0000-0001-6857-5810"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Flach","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6857-5810","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068053033","display_name":"Raedt Luc De","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raedt Luc De","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060174190","display_name":"Nada Lavra\u010d","orcid":"https://orcid.org/0000-0002-9995-7093","observed_orcids":["https://orcid.org/0000-0002-9995-7093"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nada Lavra\u010d","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9995-7093","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123981490","display_name":"Stefan Kramer","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefan Kramer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1935,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.89733353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.7935000061988831,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.7935000061988831,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.07029999792575836,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.026599999517202377,"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/feature-construction","display_name":"feature construction","score":0.8519999980926514},{"id":"https://openalex.org/keywords/inductive-rule-learning","display_name":"inductive rule learning","score":0.9909999966621399},{"id":"https://openalex.org/keywords/inductive-logic-programming","display_name":"inductive logic programming","score":0.9459999799728394},{"id":"https://openalex.org/keywords/rule-formation","display_name":"rule formation","score":0.6320000290870667},{"id":"https://openalex.org/keywords/body-construction","display_name":"body construction","score":0.7680000066757202},{"id":"https://openalex.org/keywords/search-strategies","display_name":"search strategies","score":0.5929999947547913},{"id":"https://openalex.org/keywords/hypothesis-generation","display_name":"hypothesis generation","score":0.5099999904632568}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6007797718048096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4417630732059479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43981972336769104},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.11753475666046143},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10759398341178894}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.4954","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.4954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bris.ac.uk/Publications/Papers/1000486.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.42.9442","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.9442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.informatik.uni-freiburg.de/~ml/icml2000_workshop/flach.ps","raw_type":"text"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/1141dff9-f894-4dcf-887c-c0f14b585324","doi":null,"is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/1141dff9-f894-4dcf-887c-c0f14b585324","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Flach, P, Luc De, R, Nada, L & Stefan, K 2000, The role of feature construction in inductive rule learning. in Proceedings of the ICML2000 workshop on Attribute-Value and Relational Learning: crossing the boundaries. 17th International Conference on Machine Learning, pp. 1 - 11. < http://www.cs.bris.ac.uk/Publications/pub_master.jsp?id=1000486 >","raw_type":"contributionToPeriodical"},{"id":"mag:2603390332","doi":null,"is_oa":false,"landing_page_url":"http://research-information.bristol.ac.uk/en/publications/the-role-of-feature-construction-in-inductive-rule-learning(1141dff9-f894-4dcf-887c-c0f14b585324)/export.html","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1484732323","https://openalex.org/W1508912896","https://openalex.org/W1536918907","https://openalex.org/W1546703439","https://openalex.org/W1553696291","https://openalex.org/W1591356244","https://openalex.org/W1610301803","https://openalex.org/W1619260253","https://openalex.org/W1806329564","https://openalex.org/W1971138308","https://openalex.org/W1999138184","https://openalex.org/W2061529719","https://openalex.org/W2104017387","https://openalex.org/W2113243831","https://openalex.org/W2119831128","https://openalex.org/W2136000097","https://openalex.org/W2138745909","https://openalex.org/W2158292827"],"related_works":["https://openalex.org/W6940960488","https://openalex.org/W2167457540","https://openalex.org/W2591623990","https://openalex.org/W2942197382","https://openalex.org/W207418710","https://openalex.org/W39499675","https://openalex.org/W787828758","https://openalex.org/W2950527584","https://openalex.org/W2165347852","https://openalex.org/W2086885439"],"abstract_inverted_index":{".":[0],"This":[1],"paper":[2],"proposes":[3],"a":[4,63,83,122],"unifying":[5],"framework":[6],"for":[7,86],"inductive":[8,21,75,126],"rule":[9,34,72,127],"learning":[10,73,106,128],"algorithms.":[11,129],"We":[12,79],"suggest":[13],"that":[14,59],"the":[15,31,68,97,116],"problem":[16],"of":[17,24,42,96,100,118],"constructing":[18,135],"an":[19],"appropriate":[20],"hypothesis":[22],"(set":[23],"rules)":[25],"can":[26],"be":[27],"broken":[28],"down":[29],"in":[30,66,125],"following":[32],"subtasks:":[33],"construction,":[35,37],"body":[36],"and":[38,53,74,114],"feature":[39,60],"construction.":[40],"Each":[41],"these":[43],"subtasks":[44],"may":[45],"have":[46],"its":[47],"own":[48],"declarative":[49],"bias,":[50],"search":[51,112],"strategies,":[52],"heuristics.":[54],"In":[55],"particular,":[56],"we":[57],"argue":[58],"construction":[61,117],"is":[62,121],"crucial":[64,123],"notion":[65],"explaining":[67],"relations":[69],"between":[70],"attribute-value":[71],"logic":[76],"programming":[77],"(ILP).":[78],"demonstrate":[80],"this":[81],"by":[82,134],"general":[84],"method":[85],"transforming":[87],"ILP":[88],"problems":[89],"to":[90],"attributevalue":[91],"form,":[92],"which":[93],"overcomes":[94],"some":[95],"traditional":[98],"limitations":[99],"propositionalisation":[101],"approaches.":[102],"1":[103],"Introduction":[104],"Rule":[105],"tasks":[107],"are":[108,132],"typically":[109],"approached":[110],"as":[111],"problems,":[113],"hence":[115],"candidate":[119],"hypotheses":[120,131],"task":[124],"Traditionally,":[130],"constructed":[133],"rules...":[136]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2017-04-07T00:00:00"}