{"created":"2020-09-01T15:07:39.390748+00:00","id":4580,"links":{},"metadata":{"_buckets":{"deposit":"80783a9b-0b95-43f4-b94e-c7e6e7d9238e"},"_deposit":{"id":"4580","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4580"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4580","sets":["1582963302567:1597824175385"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Real-time Big Data Analytics for Feature Selection on Apache Spark","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Real-time data analysis is a key research in many domains. It can be applied to pre-existing orprescriptive models. The effective result is that monitor the account and review on a real-time action. Apachespark machine learning library Mllib can be distinct display place for real-time assessment foe extracting,transforming and selecting features and classification, clustering and frequent pattern mining. Featureselection is the detection in a group of feature what are the most relevant and removing the redundant data.Specifically, we made using the Apache spark tool and analyze the streaming time-series data using Mllib toextract the high qualitative feature in efficiently to get qualitative and high performance model."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"feature selection"},{"interim":"apache spark"},{"interim":"filter method"},{"interim":"real-time data"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-03-13"}],"displaytype":"preview","filename":"LwinMayThant.pdf","filesize":[{"value":"178 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4580/files/LwinMayThant.pdf"},"version_id":"822e3257-bcbb-4cb6-9ee5-f30f1389703b"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Proceedings of the 10th International Workshop on Computer Science and Engineering (WCSE 2020)","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":"Thant, Lwin May"},{"subitem_authors_fullname":"Phyu, Sabai"}]}]},"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":"2020-02-28"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"ISBN 978-981-14-4787-7"},"item_title":"Real-time Big Data Analytics for Feature Selection on Apache Spark","item_type_id":"21","owner":"1","path":["1597824175385"],"publish_date":"2020-03-13","publish_status":"0","recid":"4580","relation_version_is_last":true,"title":["Real-time Big Data Analytics for Feature Selection on Apache Spark"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T06:19:06.956521+00:00"}