{"_buckets": {"deposit": "d8a279f8-cf03-45ed-a6bd-1ff79bc11ed6"}, "_deposit": {"id": "5087", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "5087"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5087"}, "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Stock Trend Prediction from Mobile Device through Web Services", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "This paper presents a study of regression analysisfor use in stock price prediction. The system showsthe stock market trend of the specified bank usingthe previous stock prices. Data were obtainedfrom the daily official list of the prices of allshares traded on the stock exchange. Androiddevices invoke stock price prediction process viarestful web service. In the server side, the datamining process uncovers patterns andrelationships and also extracts values of variablesfrom the database to predict the future values ofother variables through the use of time series datathat employed moving average method. The datamining process predicts the trend of the futurestock market price. The predicted result is sent asJSON response to android device. Android clientshows the result with graph lines to supportinvestors for decision making in stock market. Forreducing the risk in stock investment, the investorscan see the predicted trends of the companiescomparing in one graph diagram and makedecisions."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_name_i18n": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-18"}], "displaytype": "preview", "download_preview_message": "", "filename": "84_PDFsam_PSC_final proof.pdf", "filesize": [{"value": "137 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 137000, "url": {"url": "https://meral.edu.mm/record/5087/files/84_PDFsam_PSC_final proof.pdf"}, "version_id": "5d9cd113-aae2-4542-9cff-2b045202926d"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Eighth 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": "Aung, Kay Thi"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_name_i18n": "Upload type", "attribute_value": "Publication"}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_name_i18n": "Publication type", "attribute_value": "Article"}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_name_i18n": "Publication date", "attribute_value": "2017-12-27"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/977"}, "item_title": "Stock Trend Prediction from Mobile Device through Web Services", "item_type_id": "21", "owner": "1", "path": ["1582963302567/1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005087", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-18"}, "publish_date": "2019-07-18", "publish_status": "0", "recid": "5087", "relation": {}, "relation_version_is_last": true, "title": ["Stock Trend Prediction from Mobile Device through Web Services"], "weko_shared_id": -1}