• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.129-146
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• 2010

Nowadays, XML has been favored by many companies internally and externally as a means of sharing and distributing data. there are many researches and systems for modeling and storing XML documents by an object-oriented method as for the method of saving and managing web-based multimedia document more easily. The representative tool for the object-oriented modeling of XML documents is UML (Unified Modeling Language). UML at the beginning was used as the integrated methodology for software development, but now it is used more frequently as the modeling language of various objects. Currently, UML supports various diagrams for object-oriented analysis and design like class diagram and is widely used as a tool of creating various database schema and object-oriented codes from them. This paper proposes an Efficinet Query Modelling of XML-GL using the UML class diagram and OCL for searching XML document which its application scope is widely extended due to the increased use of WWW and its flexible and open nature. In order to accomplish this, we propose the modeling rules and algorithm that map XML-GL. which has the modeling function for XML document and DTD and the graphical query function about that. In order to describe precisely about the constraint of model component, it is defined by OCL (Object Constraint Language). By using proposed technique creates a query for the XML document of holding various properties of object-oriented model by modeling the XML-GL query from XML document, XML DTD, and XML query while using the class diagram of UML. By converting, saving and managing XML document visually into the object-oriented graphic data model, user can prepare the base that can express the search and query on XML document intuitively and visually. As compared to existing XML-based query languages, it has various object-oriented characteristics and uses the UML notation that is widely used as object modeling tool. Hence, user can construct graphical and intuitive queries on XML-based web document without learning a new query language. By using the same modeling tool, UML class diagram on XML document content, query syntax and semantics, it allows consistently performing all the processes such as searching and saving XML document from/to object-oriented database.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.339-352
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• 2009

There are a number of formal methods for distributed real-time systems in ubiquitous computing to analyze and verify the behavioral, temporal and the spatial properties of the systems. However most of the methods reveal structural and fundamental limitations of complexity due to mixture of spatial and behavioral representations. Further temporal specification makes the complexity more complicate. In order to overcome the limitations, this paper presents a new formal method, called Timed Calculus of Abstract Real-Time Distribution, Mobility and Interaction(t-CARDMI). t-CARDMI separates spatial representation from behavioral representation to simplify the complexity. Further temporal specification is permitted only in the behavioral representation to make the complexity less complicate. The distinctive features of the temporal properties in t-CARDMI include waiting time, execution time, deadline, timeout action, periodic action, etc. both in movement and interaction behaviors. For analysis and verification of spatial and temporal properties of the systems in specification, t-CARDMI presents Timed Action Graph (TAG), where the spatial and temporal properties are visually represented in a two-dimensional diagram with the pictorial distribution of movements and interactions. t-CARDMI can be considered to be one of the most innovative formal methods in distributed real-time systems in ubiquitous computing to specify, analyze and verify the spatial, behavioral and the temporal properties of the systems very efficiently and effectively. The paper presents the formal syntax and semantics of t-CARDMI with a tool, called SAVE, for a ubiquitous healthcare application.

• Cross-Cultural Studies
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• v.53
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• pp.163-192
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• 2018

The purpose of this paper was to examine universal dependency UD application cases of Korean and Japanese with similar morphological characteristics. In addition, UD application and improvement methods of Korean were examined through comparative analysis. Korean and Japanese are very well developed due to their agglutinative characteristics. Therefore, there are many difficulties to apply UD which is built around English refraction. We examined the application of UPOS and DEPREL as components of UD with discussions. In UPOS, we looked at category problem related to narrative such as AUX, ADJ, and VERB, We examined how to handle units. In relation to the DEPREL annotation system, we discussed how to reflect syntactic problem from the basic unit annotation of syntax tags. We investigated problems of case and aux arising from the problem of setting dominant position from Korean and Japanese as the dominant language. We also investigated problems of annotation of parallel structure and setting of annotation basic unit. Among various relation annotation tags, case and aux are discussed because they show the most noticeable difference in distribution when comparing annotation tag application patterns with Korean. The case is related to both Korean and Japanese surveys. Aux is a secondary verb in Korean and an auxiliary verb in Japanese. As a result of examining specific annotation patterns, it was found that Japanese aux not only assigned auxiliary clauses, but also auxiliary elements to add the grammatical meaning to the verb and form corresponding to the end of Korean. In UD annotation of Japanese, the basic unit of morphological analysis is defined as a unit of basic syntactic annotation in Japanese UD annotation. Thus, when using information, it is necessary to consider how to use morphological analysis unit as information of dependency annotation in Korean.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.