{"_buckets": {"deposit": "af282deb-bf45-4175-8282-3d10284d11f0"}, "_deposit": {"id": "4550", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4550"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4550", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Retrieving Semantically Relevant Documents using Latent Semantic Indexing", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, with the development of the internet, it is available to collect verylarge amounts of data and searching effective information from these data developinto an essential work. The major purpose of an Information Retrieval system is toretrieve all the relevant documents, which are relevant to the user query. Popularsearch engines such as Google, Yahoo, Alta Vista and Bing give the services of theform of modern information retrieval.Term matching techniques may retrieve irrelevant or inaccurate resultsbecause of synonyms and polysemys words, so effective concept-based techniques areneeded. This system examines the utility of conceptual indexing to improve retrievalperformance of a domain specific information retrieval system using Latent SemanticIndexing (LSI). LSI is an indexing and retrieval method that uses a mathematicaltechnique called Singular Value Decomposition (SVD) to figure out patterns in therelationship between the term used and the meaning they convey. LSI makes use ofthe words that occur together in documents to capture the hidden related meaningsamong documents and thus can improve the ability to rank relevant documents.This system is able to accept a user query such as a phrase or sentences, searchthe most semantically related documents and rank and retrieve such documentsaccording to their similarity values. In this system, Cosine Similarity Method is usedto find the relevancy and also let the user to view the results by descending order ofthe similarity values. This system ensures to support the searching time and providethe rate of latent semantic relevancy. The accuracy result of the system is calculatedby precision, recall and f-measure. This system introduces to search the symptomsand signs of disease which are collected from https://www.medicinenet.com/symptoms and signs/symptomchecker.htm#introView. It basically works as a webpage search system. The proposed system expected that it helps the people who wantto find the information about biomedical diseases."}]}, "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": "2020-01-22"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "5MCS-155 Chue Wut Yee Book.pdf", "filesize": [{"value": "2223 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2223000.0, "url": {"url": "https://meral.edu.mm/record/4550/files/5MCS-155 Chue Wut Yee Book.pdf"}, "version_id": "adbaf9ab-ad85-41e2-876b-b15903865bd7"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "", "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": "Unversity of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Yee, Chue Wut"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2020-01"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2472"}, "item_title": "Retrieving Semantically Relevant Documents using Latent Semantic Indexing", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004550", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-01-22"}, "publish_date": "2020-01-22", "publish_status": "0", "recid": "4550", "relation": {}, "relation_version_is_last": true, "title": ["Retrieving Semantically Relevant Documents using Latent Semantic Indexing"], "weko_shared_id": -1}