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PC-KIMMO-based Description of Mongolian Morphology
Jaimai, Purev,Zundui, Tsolmon,Chagnaa, Altangerel,Ock, Cheol-Young Korea Information Processing Society 2005 Journal of information processing systems Vol.1 No.1
This paper presents the development of a morphological processor for the Mongolian language, based on the two-level morphological model which was introduced by Koskenniemi. The aim of the study is to provide Mongolian syntactic parsers with more effective information on word structure of Mongolian words. First hand written rules that are the core of this model are compiled into finite-state transducers by a rule tool. Output of the compiler was edited to clarity by hand whenever necessary. The rules file and lexicon presented in the paper describe the morphology of Mongolian nouns, adjectives and verbs. Although the rules illustrated are not sufficient for accounting all the processes of Mongolian lexical phonology, other necessary rules can be easily added when new words are supplemented to the lexicon file. The theoretical consideration of the paper is concluded in representation of the morphological phenomena of Mongolian by the general, language-independent framework of the two-level morphological model.
Representing Unish Grammars Based on Tree Adjoining Grammar Formalisms
Jaimai, Purev,Park, Hyun Seok Institute for University Language Sejong Instituti 2003 Journal of Universal Language Vol.4 No.1
To make any sort of optimality argument, or rational engineering decision, one needs a fairly precise understanding of the problem to be tackled. Thus the purpose of this paper is to formalize Unish grammar by developing prototype Unish Tree Adjoining Grammars in the hope that developing and formalizing Unish grammars at this stage will help to direct the way the future version of Unish should be tailored and modified, as an artificial language.
English-Mongolian Machine Translation Prototype System
Chagnaa Altangerel,Jaimai Purev,Munkhjargal Zoljargal,Cheol-Young Ock 한국멀티미디어학회 2011 한국멀티미디어학회 국제학술대회 Vol.2011 No.-
In this paper we introduce English-Mongolian machine translation system, development tools for its resources and its web application. Mongolian is a less computationally studied language in Asia. Also English and Mongolian are very different languages in such as word order. Thus, developing such a system is a challenging task. This paper introduces English-Mongolian MT engine, development tools for its resources and its web-based application in the following sections. The demo version of the system is put online.
English to Mongolian Generation Module
Dambasuren Nanzadragchaa,Jaimai Purev 한국멀티미디어학회 2011 한국멀티미디어학회 국제학술대회 Vol.2011 No.-
Recently, machine translation system for natural language has been developing in the most of the advanced countries by studying the structure of one’s natural language and introducing grammar system and certain structure using modern progressive technology. It is mainly used in performing the translation service in timely and expedite manner. More importantly, the machine traslation system is great contribution and investment in the future toward the prospect of its natural language heritage through adapting the structure and laws of one’s natural language. This work consists of two components: grammar generator software for generating mongolian sentences and an API to be used in translation system.
Mongolian Trigram Part-of-Speech Tagger
Zoljargal Munkhjargal,Purev Jaimai 한국멀티미디어학회 2011 한국멀티미디어학회 국제학술대회 Vol.2011 No.-
This paper presents a trigram part-of-speech tagger for Mongolian which is important to a large corpus because hand annotating is complicated task and assigning POS tags to each word is very time consuming.
Feature Extraction of Concepts by Independent Component Analysis
Chagnaa, Altangerel,Ock, Cheol-Young,Lee, Chang-Beom,Jaimai, Purev Korea Information Processing Society 2007 Journal of information processing systems Vol.3 No.1
Semantic clustering is important to various fields in the modem information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a hierarchical clustering in latent semantic space for finding out invisible information from the data.