{"id":"https://openalex.org/W2158838939","doi":"https://doi.org/10.1145/2801948.2802022","title":"Ranking tokens with class label frequencies for medical article classification","display_name":"Ranking tokens with class label frequencies for medical article classification","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2158838939","doi":"https://doi.org/10.1145/2801948.2802022","mag":"2158838939"},"language":"en","primary_location":{"id":"doi:10.1145/2801948.2802022","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2801948.2802022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Panhellenic Conference on Informatics","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/A5038986091","display_name":"Kostas Fragos","orcid":null},"institutions":[{"id":"https://openalex.org/I40479246","display_name":"Technological Educational Institute of Athens","ror":"https://ror.org/044m46d61","country_code":"GR","type":"education","lineage":["https://openalex.org/I40479246"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Kostas Fragos","raw_affiliation_strings":["Technological Educational institute of Athens (TEIA), Athens"],"affiliations":[{"raw_affiliation_string":"Technological Educational institute of Athens (TEIA), Athens","institution_ids":["https://openalex.org/I40479246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076652315","display_name":"Christos Skourlas","orcid":"https://orcid.org/0000-0003-4464-5305"},"institutions":[{"id":"https://openalex.org/I40479246","display_name":"Technological Educational Institute of Athens","ror":"https://ror.org/044m46d61","country_code":"GR","type":"education","lineage":["https://openalex.org/I40479246"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Christos Skourlas","raw_affiliation_strings":["TEI of Athens, Athens"],"affiliations":[{"raw_affiliation_string":"TEI of Athens, Athens","institution_ids":["https://openalex.org/I40479246"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038986091"],"corresponding_institution_ids":["https://openalex.org/I40479246"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76500815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1994","issue":null,"first_page":"359","last_page":"360"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9948999881744385,"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/computer-science","display_name":"Computer science","score":0.7631113529205322},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7045938372612},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6392959356307983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6287950277328491},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5947751402854919},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5115469694137573},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4602258801460266},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4548431634902954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4425833225250244},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42774567008018494},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4224066734313965},{"id":"https://openalex.org/keywords/document-classification","display_name":"Document classification","score":0.41404715180397034}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7631113529205322},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7045938372612},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6392959356307983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6287950277328491},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5947751402854919},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5115469694137573},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4602258801460266},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4548431634902954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4425833225250244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42774567008018494},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4224066734313965},{"id":"https://openalex.org/C2780479914","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Document classification","level":2,"score":0.41404715180397034},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2801948.2802022","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2801948.2802022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Panhellenic Conference on Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W2011578637","https://openalex.org/W2030122528","https://openalex.org/W2057175746","https://openalex.org/W2063702296","https://openalex.org/W2071232188","https://openalex.org/W2071664212","https://openalex.org/W2116062530","https://openalex.org/W2118830253","https://openalex.org/W2137291015","https://openalex.org/W2147169507","https://openalex.org/W2157751635","https://openalex.org/W2716341162","https://openalex.org/W2952879406","https://openalex.org/W4243672572","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2943022475","https://openalex.org/W2074769550","https://openalex.org/W3031069236","https://openalex.org/W4313397532","https://openalex.org/W4313203076","https://openalex.org/W4389115964","https://openalex.org/W3096211175","https://openalex.org/W4281776617","https://openalex.org/W3049000890","https://openalex.org/W4385339003"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,41,63],"new":[4],"method":[5,28,94],"for":[6],"medical":[7,49,87],"article":[8,51],"classification":[9,78],"is":[10],"proposed":[11,27,95],"based":[12],"on":[13,83],"exploiting":[14],"information":[15],"from":[16],"local":[17,56],"and":[18,52,57],"global":[19,58],"class":[20,59],"label":[21,60],"frequencies":[22,61],"in":[23,47,62,77],"training":[24],"corpus.":[25],"The":[26,80],"partially":[29],"overcomes":[30],"the":[31,48,74,84,93],"low":[32],"accuracy":[33],"rate":[34],"of":[35,86],"KNN":[36,100],"classifier.":[37],"First,":[38],"it":[39,54],"uses":[40,55],"lexical":[42],"approach":[43],"to":[44,67,72],"identify":[45],"tokens":[46],"document":[50],"then,":[53],"sophisticated":[64],"way":[65],"similar":[66],"traditional":[68,99],"tf-idf":[69],"weighting":[70],"scheme":[71],"devise":[73],"weighted":[75],"function":[76],"process.":[79],"evaluation":[81],"experiments":[82],"collection":[85],"documents,":[88],"called":[89],"Ohsumed,":[90],"show":[91],"that":[92],"here":[96],"significantly":[97],"outperforms":[98],"classification.":[101]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}