{"created":"2020-09-01T09:58:42.719558+00:00","id":3342,"links":{},"metadata":{"_buckets":{"deposit":"05d2c48b-c40d-439a-865e-57aff7ff42ea"},"_deposit":{"id":"3342","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3342"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3342","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Text Classification Using Naïve Bayesian Classifier with Bigram","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Classification is a form of data analysis that canbe used to extract models describing important dataclasses or to predict future data trends. Dataclassification is a two step process. This system is tostudy the Naïve Bayesian Classifier and to classifythe class labels of data sets. In this system, classifieris built on the training data sets and tests theunknown datasets. And then, calculate the accuracyof classifier by using F1-Measure (F1-score). TheNaïve Bayesian (NB) classifiers have been one of themost popular techniques as basis of manyclassification applications both theoretically andpractically. Before the classifier is built, standardtext documents are read, remove stop words andpunctuations, stemming the words by using PorterStemming Algorithm and then features are extractedby using Bigram probability based on keywords suchas preprocessing step. The experiment is performedon IEEE and ACM standard documents, researchdocuments. This system is determined the kind ofdocument, such as medicine, computer, engineeringand agriculture by using Naïve Bayesian Classifier."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-22"}],"displaytype":"preview","filename":"psc2010paper (166).pdf","filesize":[{"value":"183 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3342/files/psc2010paper (166).pdf"},"version_id":"397a2380-7844-4c49-9638-4104a433e2fe"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fifth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Tin, Thandar"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2010-12-16"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1102"},"item_title":"Text Classification Using Naïve Bayesian Classifier with Bigram","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-22","publish_status":"0","recid":"3342","relation_version_is_last":true,"title":["Text Classification Using Naïve Bayesian Classifier with Bigram"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T05:51:03.092568+00:00"}