{"created":"2020-09-01T14:50:28.735189+00:00","id":4453,"links":{},"metadata":{"_buckets":{"deposit":"cc37c610-5235-45f4-9258-4a52e4785e6a"},"_deposit":{"id":"4453","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4453"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4453","sets":["1582963302567:1597824322519"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Joint Word Segmentation and Stemming for Myanmar Language","subitem_1551255648112":"en_US"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Due to the powerful development of internet use, the amount of unstructuredMyanmar text data has increased excessively. It is necessary to retrieve exact data foruser query. The effectiveness of searching is obviously related to the stemming process.Identifying the stem word in a given text is an important aspect of any Natural LanguageProcess. In Myanmar language, texts typically contain many different forms of a basicword. Morphological variants are generally the most common problem in mis-spellings,wrong translation and irrelevant retrieval query.Since Myanmar written language does not use blank spaces to indicate wordboundaries, segmenting Myanmar texts becomes an essential task for Myanmarlanguage processing. Besides word segmentation, it is necessary to identify the stemwords in the sentence. Stemming refers to the process of marking each word in the wordsegmentation result with a correct word type, for example, root word, single word,prefix, suffix, etc. The segmentation and stemming process are denoted asmorphological analysis. During the process of word segmentation, two main problemsoccur: segmentation ambiguities and unknown word occurrences. There are basicallytwo types of segmentation ambiguities: covering ambiguity and overlapping ambiguity.These ambiguities are dealt with known words. An unknown word is defined as a wordthat is not found in the system dictionary. In other words, it is an out-of-vocabularyword. For any languages, even the largest dictionary will not be capable of registeringall geographical names, person names, organization names, technical terms and someduplication words, etc. Named entity recognition (NER), refers to recognizing entitiesthat have specific meanings in the identified text, including persons, locations,organization, etc.Normally, stemming is considered as a separate process from segmentation. Inthis new approach, segmentation, stemming and named entity detection are integratedas a lexical analysis system. This research contributes to integrate segmentation,stemming and named entity detection that would benefit in all these process. Althoughmany stemmers are available for the major languages, there is no stemmer for MyanmarLanguage. The main reason is to produce Myanmar stemmer and it also solves the wordsegmentation problem and detects the named entities. This is the first work on jointMyanmar word segmentation, stemming and named entity detection.ivNowadays, deep learning approaches have become more and more popular inNLP tasks. This system proposes BiLSTM-CNN-CRF network architecture that jointlylearns three processes. In this approach, stemming and named entity detection areconsidered as a typical sequence tagging problem over segmented words, whilesegmentation also can be modelled as a syllable-level tagging problem that identify theword boundaries via predicting the labels. This approach is an effective joint neuralsequence labelling which predicts the combinatory labels of segmentation boundariesand stemming and named entity detection tag at the syllable level.This research presents BiLSTM-CNN-CRF architecture that learns bothcharacter and syllable-level features, presenting the first evaluating of such architectureon Myanmar language evaluation datasets. This research also evaluates over differentnetwork architecture and many hyper parameters optimization such as pre-trainedembedding, dropout rate, learning rate and different optimizers."}]},"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":"2019-11-13"}],"displaytype":"preview","filename":"Joint Word Segmentation and Stemming for Myanmar Language(9Ph.D-17).pdf","filesize":[{"value":"4490 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4453/files/Joint Word Segmentation and Stemming for Myanmar Language(9Ph.D-17).pdf"},"version_id":"51943003-bdf5-414c-bc8f-d57fea60e344"}]},"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":"University of Computer Studies, Yangon","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Oo, Yadanar"}]}]},"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":"2019-10"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/2384"},"item_title":"Joint Word Segmentation and Stemming for Myanmar Language","item_type_id":"21","owner":"1","path":["1597824322519"],"publish_date":"2019-11-13","publish_status":"0","recid":"4453","relation_version_is_last":true,"title":["Joint Word Segmentation and Stemming for Myanmar Language"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2022-03-24T23:12:16.233245+00:00"}