{"id":"https://openalex.org/W2153752143","doi":null,"title":"Extraction Patterns for Information Extraction Tasks: A Survey","display_name":"Extraction Patterns for Information Extraction Tasks: A Survey","publication_year":1999,"publication_date":"1999-01-01","ids":{"openalex":"https://openalex.org/W2153752143","mag":"2153752143"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.531.3434","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.531.3434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aaai.org/Papers/Workshops/1999/WS-99-11/WS99-11-001.pdf","raw_type":"text"},"volume":null,"type":"conference-paper","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/A5011344987","display_name":"Ion Muslea","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ion Muslea","raw_affiliation_strings":["Information Sciences Institute#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute#TAB#","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5011344987"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.5397,"has_fulltext":false,"cited_by_count":225,"citation_normalized_percentile":{"value":0.99159664,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.5874000191688538,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.5874000191688538,"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":0.15549999475479126,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.11129999905824661,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/information-extraction","display_name":"information extraction","score":0.9599999785423279},{"id":"https://openalex.org/keywords/extraction-patterns","display_name":"extraction patterns","score":0.9950000047683716},{"id":"https://openalex.org/keywords/pattern-generation","display_name":"pattern generation","score":0.628000020980835},{"id":"https://openalex.org/keywords/machine-learning","display_name":"machine learning","score":0.8410000205039978}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122989892959595},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.6941040754318237},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5591276288032532},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5253747701644897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5115255117416382},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.42878037691116333},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4279642105102539},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4107290506362915},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3844999372959137},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.531.3434","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.531.3434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aaai.org/Papers/Workshops/1999/WS-99-11/WS99-11-001.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.67.4784","doi":null,"is_oa":false,"landing_page_url":"https://web.archive.org/web/20130430153622/http://www.isi.edu/~muslea/PS/ml4ie-aaai99.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isi.edu/~muslea/PS/ml4ie-aaai99.pdf","raw_type":"text"},{"id":"mag:2153752143","doi":null,"is_oa":false,"landing_page_url":"http://staf.cs.ui.ac.id/WebKuliah/SeminarB2004/ml4ie-aaai99.pdf","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":14,"referenced_works":["https://openalex.org/W1502749598","https://openalex.org/W1553019137","https://openalex.org/W1553229631","https://openalex.org/W2033209333","https://openalex.org/W2046491822","https://openalex.org/W2065568440","https://openalex.org/W2081580037","https://openalex.org/W2137096228","https://openalex.org/W2143349571","https://openalex.org/W2147810216","https://openalex.org/W2153072229","https://openalex.org/W2162340487","https://openalex.org/W2164949130","https://openalex.org/W3089319657"],"related_works":["https://openalex.org/W7098869493","https://openalex.org/W3122604748","https://openalex.org/W7036829383","https://openalex.org/W1997553786","https://openalex.org/W7099883080","https://openalex.org/W67152270","https://openalex.org/W7101100702","https://openalex.org/W7098855873","https://openalex.org/W1842945429","https://openalex.org/W1565862766"],"abstract_inverted_index":{"Information":[0],"Extraction":[1],"systems":[2],"rely":[3],"on":[4],"a":[5,50],"set":[6],"of":[7,31,46,52],"extraction":[8,32],"patterns":[9,33,61],"that":[10,34],"they":[11],"use":[12],"in":[13],"order":[14],"to":[15],"retrieve":[16],"from":[17,62],"each":[18,63],"docu-ment":[19],"the":[20,28,60],"relevant":[21],"information.":[22],"In":[23],"this":[24],"paper":[25],"we":[26,56],"survey":[27],"various":[29],"types":[30],"are":[35],"generated":[36],"by":[37],"ma-chine":[38],"learning":[39],"algorithms.":[40],"We":[41],"identify":[42],"three":[43],"main":[44],"categories":[45],"patterns,":[47],"which":[48],"cover":[49],"variety":[51],"application":[53],"domains,":[54],"and":[55,58],"compare":[57],"contrast":[59],"category.":[64]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":16}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
