{"id":"https://openalex.org/W1995709288","doi":"https://doi.org/10.1142/s0218001408006247","title":"POLYNOMIAL NETWORKS VERSUS OTHER TECHNIQUES IN TEXT CATEGORIZATION","display_name":"POLYNOMIAL NETWORKS VERSUS OTHER TECHNIQUES IN TEXT CATEGORIZATION","publication_year":2008,"publication_date":"2008-03-01","ids":{"openalex":"https://openalex.org/W1995709288","doi":"https://doi.org/10.1142/s0218001408006247","mag":"1995709288"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001408006247","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001408006247","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5023836922","display_name":"Mayy M. Al-Tahrawi","orcid":"https://orcid.org/0000-0001-6600-7203"},"institutions":[{"id":"https://openalex.org/I104941359","display_name":"Al-Ahliyya Amman University","ror":"https://ror.org/00xddhq60","country_code":"JO","type":"education","lineage":["https://openalex.org/I104941359"]}],"countries":["JO"],"is_corresponding":true,"raw_author_name":"MAYY M. AL-TAHRAWI","raw_affiliation_strings":["Al-Ahliyya Amman University, P.O. Box 348, Amman 19374, Jordan"],"affiliations":[{"raw_affiliation_string":"Al-Ahliyya Amman University, P.O. Box 348, Amman 19374, Jordan","institution_ids":["https://openalex.org/I104941359"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078607983","display_name":"Raed Abu Zitar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104314","display_name":"New York Institute of Technology","ror":"https://ror.org/01bghzb51","country_code":"US","type":"education","lineage":["https://openalex.org/I4210104314"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"RAED ABU ZITAR","raw_affiliation_strings":["New York Institute of Technology, P.O. Box 8401, Amman 11121, Jordan"],"affiliations":[{"raw_affiliation_string":"New York Institute of Technology, P.O. Box 8401, Amman 11121, Jordan","institution_ids":["https://openalex.org/I4210104314"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023836922"],"corresponding_institution_ids":["https://openalex.org/I104941359"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.06210693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"22","issue":"02","first_page":"295","last_page":"322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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":0.9997000098228455,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9912999868392944,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9896000027656555,"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/computer-science","display_name":"Computer science","score":0.7841034531593323},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7366613745689392},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6879304051399231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6766781210899353},{"id":"https://openalex.org/keywords/text-categorization","display_name":"Text categorization","score":0.5727276802062988},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5420227646827698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5206565260887146},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5176194906234741},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48239266872406006},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47420671582221985},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4644226133823395},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4502987265586853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40440431237220764}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7841034531593323},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7366613745689392},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6879304051399231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6766781210899353},{"id":"https://openalex.org/C2986744138","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Text categorization","level":3,"score":0.5727276802062988},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5420227646827698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5206565260887146},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5176194906234741},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48239266872406006},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47420671582221985},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4644226133823395},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4502987265586853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40440431237220764},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001408006247","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001408006247","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1964168965","https://openalex.org/W2023450550","https://openalex.org/W2041460909","https://openalex.org/W2098162425","https://openalex.org/W2100074460","https://openalex.org/W2103333826","https://openalex.org/W2118020555","https://openalex.org/W2119821739","https://openalex.org/W2124503759","https://openalex.org/W2135346934","https://openalex.org/W2139212933","https://openalex.org/W2140785063","https://openalex.org/W2143956139","https://openalex.org/W2148603752","https://openalex.org/W2156909104","https://openalex.org/W2203146472","https://openalex.org/W2800394774","https://openalex.org/W4234819098","https://openalex.org/W4244829582"],"related_works":["https://openalex.org/W2360898036","https://openalex.org/W2390857744","https://openalex.org/W2133651098","https://openalex.org/W2390698788","https://openalex.org/W2035261173","https://openalex.org/W2138922887","https://openalex.org/W2383063829","https://openalex.org/W2082678934","https://openalex.org/W2106892947","https://openalex.org/W2237299843"],"abstract_inverted_index":{"Many":[0],"techniques":[1,36],"and":[2,11,77,108,127,140,158],"algorithms":[3,30],"for":[4,22,37],"automatic":[5],"text":[6,38],"categorization":[7,39],"had":[8],"been":[9],"devised":[10],"proposed":[12,84],"in":[13,24,48,59,81,93,103,124],"the":[14,55,64,113,120,128,137,143,152,159],"literature.":[15],"However,":[16],"there":[17],"is":[18,101],"still":[19],"much":[20],"space":[21],"researchers":[23],"this":[25,73,98],"area":[26],"to":[27,54],"improve":[28],"existing":[29],"or":[31],"come":[32],"up":[33],"with":[34],"new":[35],"(TC).":[40],"Polynomial":[41],"Networks":[42],"(PNs)":[43],"were":[44],"never":[45],"used":[46,58],"before":[47],"TC.":[49,82],"This":[50],"can":[51],"be":[52],"attributed":[53],"huge":[56],"datasets":[57,123],"TC,":[60],"as":[61,63],"well":[62],"technique":[65],"itself":[66],"which":[67],"has":[68,87],"high":[69,99],"computational":[70],"demands.":[71],"In":[72],"paper,":[74],"we":[75],"investigate":[76],"propose":[78],"using":[79,109],"PNs":[80],"The":[83],"PN":[85],"classifier":[86],"achieved":[88,102],"a":[89],"competitive":[90],"classification":[91],"performance":[92,100],"our":[94],"experiments.":[95],"More":[96],"importantly,":[97],"one":[104],"shot":[105],"training":[106],"(noniteratively)":[107],"just":[110],"0.25%\u20130.5%":[111],"of":[112],"corpora":[114],"features.":[115],"Experiments":[116],"are":[117,134],"conducted":[118],"on":[119,136],"two":[121],"benchmark":[122],"TC:":[125],"Reuters-21578":[126],"20":[129],"Newsgroups.":[130],"Five":[131],"well-known":[132],"classifiers":[133],"experimented":[135],"same":[138],"data":[139],"feature":[141],"subsets:":[142],"state-of-the-art":[144],"Support":[145],"Vector":[146],"Machines":[147],"(SVM),":[148],"Logistic":[149],"Regression":[150],"(LR),":[151],"k-nearest-neighbor":[153],"(kNN),":[154],"Naive":[155],"Bayes":[156],"(NB),":[157],"Radial":[160],"Basis":[161],"Function":[162],"(RBF)":[163],"networks.":[164]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}