{"id":"https://openalex.org/W2148053532","doi":"https://doi.org/10.1109/icdm.2003.1250979","title":"Effectiveness of information extraction, multi-relational, and semi-supervised learning for predicting functional properties of genes","display_name":"Effectiveness of information extraction, multi-relational, and semi-supervised learning for predicting functional properties of genes","publication_year":2004,"publication_date":"2004-03-30","ids":{"openalex":"https://openalex.org/W2148053532","doi":"https://doi.org/10.1109/icdm.2003.1250979","mag":"2148053532"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250979","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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/A5036715304","display_name":"Mark-A. Krogel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210138551","display_name":"University Hospital Magdeburg","ror":"https://ror.org/03m04df46","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I4210138551"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"M.-A. Krogel","raw_affiliation_strings":["FIN/IWS, University of Magdeburg, Magdeburg, Germany"],"affiliations":[{"raw_affiliation_string":"FIN/IWS, University of Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I4210138551"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007427935","display_name":"Tobias Scheffer","orcid":"https://orcid.org/0000-0003-4405-7925"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"T. Scheffer","raw_affiliation_strings":["Department of Computer Science, Humboldt University of Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Humboldt University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036715304"],"corresponding_institution_ids":["https://openalex.org/I4210138551"],"apc_list":null,"apc_paid":null,"fwci":1.5781,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89545507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"569","last_page":"572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9955999851226807,"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":0.9955999851226807,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6754579544067383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6527225375175476},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5797638297080994},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5125627517700195},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4837658405303955},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.4603568911552429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45971277356147766},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.4105321764945984},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32492178678512573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1304311454296112}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6754579544067383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6527225375175476},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5797638297080994},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5125627517700195},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4837658405303955},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4603568911552429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45971277356147766},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.4105321764945984},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32492178678512573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1304311454296112},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm.2003.1250979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250979","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W285831519","https://openalex.org/W1545331097","https://openalex.org/W1572684271","https://openalex.org/W1592053870","https://openalex.org/W2048679005","https://openalex.org/W2069116068","https://openalex.org/W2107008379","https://openalex.org/W2155653793","https://openalex.org/W6610403525","https://openalex.org/W6676132248"],"related_works":["https://openalex.org/W2112835755","https://openalex.org/W4291951920","https://openalex.org/W2349674371","https://openalex.org/W2097495471","https://openalex.org/W1696545756","https://openalex.org/W2952827811","https://openalex.org/W2056202066","https://openalex.org/W2963262648","https://openalex.org/W4301867002","https://openalex.org/W2489933339"],"abstract_inverted_index":{"We":[0,50,59,70],"focus":[1],"on":[2],"the":[3,10,16,24,72,101,109,117,123,127,131],"problem":[4,38],"of":[5,9,26,47,74,81,91,122],"predicting":[6],"functional":[7],"properties":[8],"proteins":[11],"corresponding":[12],"to":[13,22],"genes":[14],"in":[15,36,107,115,135],"yeast":[17],"genome.":[18],"Our":[19],"goal":[20],"is":[21],"study":[23,51,71],"effectiveness":[25],"approaches":[27],"that":[28,33],"utilize":[29],"all":[30],"data":[31],"sources":[32],"are":[34,87],"available":[35],"this":[37],"setting,":[39],"including":[40],"unlabeled":[41,57],"and":[42,45,53,93,126],"relational":[43,66],"data,":[44],"abstracts":[46],"research":[48],"papers.":[49],"transduction":[52],"co-training":[54],"for":[55,77,104,112,120,130],"using":[56],"data.":[58,69],"investigate":[60],"a":[61,79],"propositionalization":[62],"approach":[63],"which":[64,97],"uses":[65],"gene":[67],"interaction":[68],"benefit":[73],"information":[75],"extraction":[76],"utilizing":[78],"collection":[80],"scientific":[82],"abstracts.":[83],"The":[84,95],"studied":[85],"tasks":[86,90],"KDD":[88],"Cup":[89],"2001":[92],"2002.":[94,136],"solutions":[96],"we":[98],"describe":[99],"achieved":[100],"highest":[102,118],"score":[103,119],"task":[105,113,133],"2":[106,134],"2001,":[108,116],"fourth":[110],"rank":[111],"3":[114],"one":[121],"two":[124],"subtasks":[125],"third":[128],"place":[129],"overall":[132]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
