Language resources are most important in the computational processing of natural languages. Language resources in natural language processing include all language-related resources in convenient forms, such as voice language, text language, original a...
Language resources are most important in the computational processing of natural languages. Language resources in natural language processing include all language-related resources in convenient forms, such as voice language, text language, original and analyzed corpus, electronic dictionary, lexical network, and ontology, which are developed from processing and storing all the results of human linguistic activities.
Among these language resources, studies on the semantic language resources with semantic and conceptual characteristics contained in activities, phenomena and states, based on the basic lexical, syntactic and discoursal meaning of natural languages, are recently active. Sense tagged corpus, lexical database, lexical classification, thesaurus, lexical network and ontology, including dictionary, are considered to be representative semantic language resources, and particularly intensive studies on thesaurus, lexical network and ontology are under going in many areas.
In particular, development of lexical networks such as Word, EuroWord, which intends to organize systematically the semantic and conceptual aspects of the natural language has a close relation with the semantic processing aimed at in natural language processing, and also the needs for lexical network are increasing in many relevant areas, such as information retrieval, machine translation, library and information science, are Korean linguistics.
That is, the lexical network, which is not the simple lexical enumeration but the database of networks of close relations between words, is rapidly emerging as a necessary language resource that is very useful academically and technically.
This study, as an actual example of the lexical network, is based on lexical semantics, the construction principle of semantic network and the natural language processing technology, and accepts, criticizes and corrects the existing construction methods for thesaurus, semantic network and ontology, and presents the construction principle and practice of the User-Word Intelligent work(U-WIN) which is an extended form of lexical network of, and also a lexical database on, the large scale Korean words.
Through this study, an extended form of lexical network is explored by presenting U-WIN, which applies lexical relations that include not only semantic relations but also conceptual relations, morphological relations and syntactic relations, and contains various information related to words, such as semantic information and extended information, in a way different with existing lexical networks that have been centered around linking structures with semantic relations.
In addition, this study intends to highlight a model of Korean lexical network by considering the validity of actual semantic and conceptual linking structures on a large scale Korean words. Also, the usability of U-WIN, including a tool for developing and managing it, is presented via some application examples using U-WIN.
The core contents of this study are described from chapter 2 to chapter 5 as follows.
Chapter 2 surveys relevant domestic and foreign studies on the lexical network, and then establishes terms and concepts used in the current studies related to the lexical network, and describes some considerations on developing the lexical network via discussing the problems of existing studies and developments.
Chapter 3 details the construction principle and practice of U-WIN.
Firstly, U-WIN is introduced, and the entire stages of the study and development are explained, and theoretical backgrounds such as lexical field theory, frame semantics, and the characteristics of Korean words are analyzed. Then, based on this analysis, the construction principle and the internal structure of U-WIN for Korean words are explained.
Secondly, the lexical relations with various information and the core structure of U-WIN are described. It is explained that the lexical relation in U-WIN has not only the semantic relation between words as in the existing lexical networks but also different relations extending to the conceptual relation, the morphological relation and the syntactic relation. Also, the semantic information and the extended information in U-WIN are explained. Through this, U-WIN is differentiated from the other domestic and foreign lexical networks in the semantic relation, internal structures, and the Korean specific conceptualization and recognition system. In addition, differences between the English lexical network and the Korean lexical network are examined by comparing Word and U-WIN using some words.
Finally, the statistical data of U-WIN in the current development status, such as the hierarchical distribution diagram by parts of speech, the constructed volume by lexical relations, are described. (Appendix 1, Appendix 2)
Chapter 4 describes a tool for developing and managing U-WIN.
In this chapter, the U-WIN development and management tool is explained by its functions, which can also be used for developing and managing other lexical networks. Also, two tools for browsing U-WIN efficiently, TBrowser used in the Touch-Graph way and MBrowser used in the plane distribution way, are introduced.
Chapter 5 describes some applications using U-WIN.
Actual usage examples and application methods are explained through some actually implemented applications, such as an analysis and generation technology of compound nouns using U-WIN, a Korean word learning system using U-WIN and a Korean dictionary, a science and technology infomation retrieval service system using U-WIN.
，韩语论文题目，韩语论文范文 |
