• Journal of KIISE
• /
• v.42 no.7
• /
• pp.901-909
• /
• 2015

In this paper, to build a parallel corpus between Korean and English in Wikipedia. We proposed a method to find similar sentences based on language resources and topic modeling. We first applied language resources(Wiki-dictionary, numbers, and online dictionary in Daum) to match word sequentially. We construct the Wiki-dictionary using titles in Wikipedia. In order to take advantages of the Wikipedia, we used translation probability in the Wiki-dictionary for word matching. In addition, we improved the accuracy of sentence similarity measuring method by using word distribution based on topic modeling. In the experiment, a previous study showed 48.4% of F1-score with only language resources based on linear combination and 51.6% with the topic modeling considering entire word distributions additionally. However, our proposed methods with sequential matching added translation probability to language resources and achieved 9.9% (58.3%) better result than the previous study. When using the proposed sequential matching method of language resources and topic modeling after considering important word distributions, the proposed system achieved 7.5%(59.1%) better than the previous study.

• Journal of Korea Society of Industrial Information Systems
• /
• v.5 no.2
• /
• pp.56-61
• /
• 2000

The quality of English to Korean Machine Translation depends on how well it deals with target word selection of verbs containing enormous ambiguity. Verb sense disambiguation can be done by using collocation, but the construction of verb collocations costs a lot of efforts and expenses. So, existing methods should be examined in the practical view points. This paper describes the practical method of target word selection using existing collocation and semantic distance computed from minimum semantic features of nouns.

• Korean Journal of Acupuncture
• /
• v.33 no.3
• /
• pp.114-120
• /
• 2016

Objectives : It aims to establish a basic rule in Korean translation of the pathway of lung meridian in Miraculous Pivot Meridian vessel. Based on the rule, We tried to make standard translation of the pathway of lung meridian in Miraculous Pivot Meridian vessel. Methods : Books needed for this study were collected through searching Kyunghee University Library(http:// khis.khu.ac.kr). Keywords included "Miraculous Pivot of Huangdi's Internal Classic". We also include the book which is generally used as a textbook in Colleges of Korean Medicine. Results : In five Chinese books, the word-spacing was used differently in four phrases. Six Korean-translated books had the different translation in three phrases. We suggested a standard Korean translation of the pathway of lung meridian in Miraculous Pivot Meridian vessel. Conclusions : This result of the study would be expected to not only be published in Korean Journal of Acupuncture but be studied more about Korean translation by experts in this field.

• International Journal of Computer Science & Network Security
• /
• v.22 no.4
• /
• pp.245-253
• /
• 2022

Commenced in 1954 by IBM, machine translation has expanded immensely, particularly in this period. Machine translation can be broken into seven main steps namely- token generation, analyzing morphology, lexeme, tagging Part of Speech, chunking, parsing, and disambiguation in words. Morphological analysis plays a major role when translating Indian languages to develop accurate parts of speech taggers and word sense. The paper presents various machine translation methods used by different researchers for Indian languages along with their performance and drawbacks. Further, the paper concentrates on parts of speech (POS) tagging in Marathi dialect using various methods such as rule-based tagging, unigram, bigram, and more. After careful study, it is concluded that for machine translation, parts of speech tagging is a major step. Also, for the Marathi language, the Hidden Markov Model gives the best results for parts of speech tagging with an accuracy of 93% which can be further improved according to the dataset.

• Cross-Cultural Studies
• /
• v.27
• /
• pp.255-289
• /
• 2012

In the course of completing a National Research Foundation project, I recently found that a handwritten Korean manuscript of The Tale of Mei Fei is kept in the Adan Collection, which is a significant scholarly discovery given that no relevant research is available. The editions of the Tale of Mei Fei available in Korea include ${\ll}$藝苑?華${\gg}$ edition, ${\ll}$說?${\gg}$ edition, and the handwritten manuscript in Korean collected in the Adan Collection. Being the only handwritten Korean translation of the work, the Tale of Mei Fei in the Adan Collection was appended by the translations of ${\ll}$한셩뎨됴비연합덕젼${\gg}$ and ${\ll}$당고종무후뎐${\gg}$. As for the practice of translation of the work, literal "word to word" translation was done for the most part of the text; some sentences were occasionally translated liberally. Also, as for the poems in the text, pronunciation of each Chinese character was provided along with the translated text.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.181-188
• /
• 2006

In this paper, we propose a search algorithm for similar example-sentences in the computer-aided translation. The search for similar examples, which is a main part in the computer-aided translation, is to retrieve the most similar examples in the aspect of structural and semantical analogy for a given query from examples. The proposed algorithm is based on the Needleman-Wunsch algorithm, which is used to measure similarity between protein or nucleotide sequences in bioinformatics. If the original Needleman-Wunsch algorithm is applied to the search for similar sentences, it is likely to fail to find them since similarity is sensitive to word's inflectional components. Therefore, we use the lemma in addition to (typographical) surface information. In addition, we use the part-of-speech to capture the structural analogy. In other word, this paper proposes the similarity metric combining the surface, lemma, and part-of-speech information of a word. Finally, we present a search algorithm with the proposed metric and present pairs contributed to similarity between a query and a found example. Our algorithm shows good performance in the area of electricity and communication.

• Journal of the Korean Professional Engineers Association
• /
• v.30 no.5
• /
• pp.42-55
• /
• 1997

• Korean Journal of Cognitive Science
• /
• v.14 no.1
• /
• pp.29-40
• /
• 2003

Cross-Language Information Retrieval (CLIR) deals with the documents in various languages by one language query. A user who uses one language can retrieve the documents in another language through CLIR system. In CLIR, query translation method is known to be more efficient. For the better performance of query translation, we need more resources like dictionary, ontology, and parallel/comparable corpus but usually not available. This paper proposes a new concept called the Common Base Axis which is adapted to Korean-English Query translation ann a new weighting method in dictionary based query translation. The essential idea is that we can express Korean and English word in one vector space by Common Base Axis and use it in calculating sense distance for query weighting. The experiments show that Common Base Axis gives us good performance without ontology and is especially good for one word query translation.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2002.02a
• /
• pp.147-156
• /
• 2002

Aligned parallel corpora have proved very useful in many natural language processing tasks, including statistical machine translation and word sense disambiguation. In this paper, we describe an alignment technique for extracting transfer mapping from the parallel corpus. During building our system and data collection, we observe that there are three types of translation approaches can be used. We especially focuses on Traditional Chinese and Simplified Chinese text lexical translation and a method for extracting transfer mappings for machine translation.

• Journal of Information Processing Systems
• /
• v.17 no.1
• /
• pp.203-212
• /
• 2021

To eliminate ambiguities in the existing methods to simplify Chinese pronunciation learning, we propose a model that can predict the pronunciation of Chinese characters automatically. The proposed model relies on a statistical machine translation (SMT) framework. In particular, we consider the components of Chinese characters as the basic unit and consider the pronunciation prediction as a machine translation procedure (the component sequence as a source sentence, the pronunciation, pinyin, as a target sentence). In addition to traditional features such as the bidirectional word translation and the n-gram language model, we also implement a component similarity feature to overcome some typos during practical use. We incorporate these features into a log-linear model. The experimental results show that our approach significantly outperforms other baseline models.