{"id":"https://openalex.org/W62735629","doi":null,"title":"Learning information extraction rules: an inductive logic programming approach","display_name":"Learning information extraction rules: an inductive logic programming approach","publication_year":2002,"publication_date":"2002-07-21","ids":{"openalex":"https://openalex.org/W62735629","mag":"62735629"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.14.8916","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.8916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aiai.ed.ac.uk/~stuart/Papers/ecai02-paper.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/A5111609904","display_name":"J. Stuart Aitken","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"J. Stuart Aitken","raw_affiliation_strings":["Artificial Intelligence Applications Institute Division of Informatics, University of Edinburgh, Edinburgh, Scotland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Applications Institute Division of Informatics, University of Edinburgh, Edinburgh, Scotland","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5111609904"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":3.0309,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.90918797,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"355","last_page":"359"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.36039999127388,"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":0.36039999127388,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.2888000011444092,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.07810000330209732,"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/information-extraction","display_name":"information extraction","score":0.9769999980926514},{"id":"https://openalex.org/keywords/inductive-logic-programming","display_name":"inductive logic programming","score":0.9079999923706055},{"id":"https://openalex.org/keywords/foil","display_name":"foil","score":0.753000020980835},{"id":"https://openalex.org/keywords/prior-knowledge","display_name":"prior knowledge","score":0.9309999942779541},{"id":"https://openalex.org/keywords/limited-training-data","display_name":"limited training data","score":0.6420000195503235},{"id":"https://openalex.org/keywords/natural-language-data","display_name":"natural language data","score":0.5080000162124634}],"concepts":[{"id":"https://openalex.org/C2779382394","wikidata":"https://www.wikidata.org/wiki/Q1464197","display_name":"Inductive logic programming","level":2,"score":0.8661882877349854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.767501711845398},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.6494148969650269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6110844016075134},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.5980396270751953},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5897490978240967},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4991269111633301},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.47051921486854553},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45629170536994934},{"id":"https://openalex.org/C2777002027","wikidata":"https://www.wikidata.org/wiki/Q3620938","display_name":"Ontology learning","level":5,"score":0.4295092821121216},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41679689288139343},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.18971160054206848},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.13864868879318237},{"id":"https://openalex.org/C137003198","wikidata":"https://www.wikidata.org/wiki/Q7247296","display_name":"Process ontology","level":3,"score":0.10355067253112793},{"id":"https://openalex.org/C50971890","wikidata":"https://www.wikidata.org/wiki/Q7635093","display_name":"Suggested Upper Merged Ontology","level":4,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.14.8916","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.8916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aiai.ed.ac.uk/~stuart/Papers/ecai02-paper.pdf","raw_type":"text"},{"id":"mag:62735629","doi":null,"is_oa":false,"landing_page_url":"https://www.frontiersinai.com/ecai/ecai2002/pdf/p0355.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306418308","display_name":"European Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"European Conference on Artificial Intelligence","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":11,"referenced_works":["https://openalex.org/W1504011958","https://openalex.org/W1531743498","https://openalex.org/W1549513557","https://openalex.org/W1553229631","https://openalex.org/W1791897581","https://openalex.org/W1954715867","https://openalex.org/W1965465660","https://openalex.org/W2026779664","https://openalex.org/W2042587746","https://openalex.org/W2081687495","https://openalex.org/W2155800811"],"related_works":["https://openalex.org/W2367318538","https://openalex.org/W2106855501","https://openalex.org/W182876327","https://openalex.org/W2079962574","https://openalex.org/W2143149090","https://openalex.org/W2000870658","https://openalex.org/W2170278674","https://openalex.org/W7095140864","https://openalex.org/W2240544104","https://openalex.org/W7100379856"],"abstract_inverted_index":{"The":[0,22],"objective":[1],"of":[2,41,60,76,81,92,104,121],"this":[3],"work":[4],"is":[5,24,51],"to":[6,18,53,63,98],"learn":[7,54],"information":[8],"extraction":[9,30],"rules":[10,31],"by":[11],"applying":[12,93],"Inductive":[13],"Logic":[14],"Programming":[15],"(ILP)":[16],"techniques":[17],"natural":[19],"language":[20],"data.":[21],"approach":[23,97],"ontology-based,":[25],"which":[26],"means":[27],"that":[28,37],"the":[29,39,44,67,73,77,79,85,89,105,110,115,119],"conclude":[32],"with":[33],"specific":[34],"ontology":[35],"relations":[36,62],"characterise":[38],"meaning":[40],"sentences":[42],"in":[43,66,84,102,108,114,118],"text.":[45,68],"An":[46],"existing":[47],"ILP":[48],"system,":[49],"FOIL,":[50],"used":[52],"attribute-value":[55],"relations.":[56],"This":[57],"enables":[58],"instances":[59],"these":[61],"be":[64],"identified":[65],"In":[69],"specific,":[70],"we":[71],"explore":[72],"linguistic":[74],"preprocessing":[75],"data,":[78],"use":[80,120],"background":[82],"knowledge":[83],"learning":[86,96],"process,":[87],"and":[88,113],"practical":[90],"considerations":[91],"a":[94],"supervised":[95],"rule":[99],"induction,":[100],"i.e.":[101],"terms":[103],"human":[106],"effort":[107],"creating":[109],"data":[111,123],"set,":[112],"inherent":[116],"biases":[117],"small":[122],"sets.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
