• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.385-398
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• 2016

This research analyzed domestic newspapers' agenda setting trend and meaning construction process on the issue of marine environment by year. The research conducted a language network analysis and used R program and Netminer program to analyze four major daily newspapers' news coverages (Dong-A, Joongang, Hanhyoreh, and Kyunghyang) for the last ten years (2005-2014). The results show that the issue of marine environment in Korean media reports are signified in the economic context. For the last ten years, news reports are mainly focused on the 'development' issue of marine environment, without distinction of year. The core key words of the networks are "development", "plan", and "project." However, diverse strategies for 'preservation' are not covered in media reports as a major issue. The importance of effective preservation and reasonable development should be considered in a balanced way. Korean media coverages mainly concentrate on the development issue, and it has a strong influence on considering the marine environment area as an object of development. Future direction and implication of the press reports related to marine environment are discussed.

• Journal of Contemporary Eastern Asia
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• v.16 no.2
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• pp.110-144
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• 2017

Unlike most languages, written Chinese has no spaces between words. Word segmentation must be performed before semantic network analysis can be conducted. This paper describes how to perform Chinese word segmentation using the Stanford Natural Language Processing group's Stanford Word Segmenter v. 3.8.0, released in June 2017.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.55-79
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• 2024

Korea, which is expected to enter a super-aged society in 2025, is facing the most worrisome crisis worldwide. Efforts are urgently required to examine problems and countermeasures from various angles and to improve the shortcomings. In this regard, from a new viewpoint, we intend to derive useful implications by applying the recent natural language processing techniques to online articles. More specifically, we derive three research questions: First, what topics are being reported in the online media and what is the public's response to them? Second, what is the relationship between these aging-related topics and individual happiness factors? Third, what are the strategic directions and implications for benchmarking discussed to solve the problem of population aging? To find answers to these, we collect Naver portal articles related to population aging and their classification categories, comments, and number of comments, including other numerical data. From the data, we firstly derive 33 topics with a semi-supervised BERTopic by reflecting article classification information that was not used in previous studies, conducting sentiment analysis of comments on them with a current open-source large language model. We also examine the relationship between the derived topics and personal happiness factors extended to Alderfer's ERG dimension, carrying out additional 3~4-gram keyword frequency analysis, trend analysis, text network analysis based on 3~4-gram keywords, etc. Through this multifaceted approach, we present diverse fresh insights from practical and theoretical perspectives.

• The Journal of Bigdata
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• v.4 no.1
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• pp.99-118
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• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.3
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• pp.327-339
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• 1986

In this paper, a hardware compiler for symbolic description language(SDL) is proposed for logic design automation. Lexical analysis is performed for SDL which describes the behavioral characteristics of a digital system at the register transfer level by the proposed algorithm I. The algorithm I is proposed to get the expressions for the control unit and for the data transfer unit. In order to obtain the network description language(NDL) expressions equivalent to gate-level logic circuits, another algorithm, the the algorithm II, is proposed. Syntax analysis for the data formed by the algorithm I is also Performed using circuit elements such as D Flip-Flop, 2-input AND, OR, and NOT gates. This SDL hardware compiler is implemented in the programming language C(VAX-11/750(UNIX)), and its efficiency is shown by experiments with logic design examples.

• Language and Information
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• v.14 no.2
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• pp.131-157
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• 2010

This article reports an attempt to perform a similarity analysis on a collection of 25 culinary manuscripts in Chosun periods using a set of quantitative text analysis methods. Historical culinary texts are valuable resources for linguistic, historic, and cultural studies. We consider the similarity of two texts as the distributional similarities of the functional components of the texts. In the case of culinary texts, text elements such as food names, cooking methods, and ingredients are regarded as functional components. We derive the similarity information from the distributional characteristics of the two key functional components, cooking methods and ingredients. The results are also quantified and visualized to achieve a better understanding of the properties of the individual texts and the collection of the texts as a whole.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.120-128
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• 2023

In this work, we have presented ATSA, a hierarchical attention deep learning model for Arabic sentiment analysis. ATSA was proposed by addressing several challenges and limitations that arise when applying the classical models to perform opinion mining in Arabic. Arabic-specific challenges including the morphological complexity and language sparsity were addressed by modeling semantic composition at the Arabic morphological analysis after performing tokenization. ATSA proposed to perform phrase-chunks sentiment embedding to provide a broader set of features that cover syntactic, semantic, and sentiment information. We used phrase structure parser to generate syntactic parse trees that are used as a reference for ATSA. This allowed modeling semantic and sentiment composition following the natural order in which words and phrase-chunks are combined in a sentence. The proposed model was evaluated on three Arabic corpora that correspond to different genres (newswire, online comments, and tweets) and different writing styles (MSA and dialectal Arabic). Experiments showed that each of the proposed contributions in ATSA was able to achieve significant improvement. The combination of all contributions, which makes up for the complete ATSA model, was able to improve the classification accuracy by 3% and 2% on Tweets and Hotel reviews datasets, respectively, compared to the existing models.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.495-501
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• 2013

The words a speaker uses can be regarded as the core, the main issue and a symbolic icon of what he says. Applying this to presidents' addresses of each English literary society in Korea shows that frequency in use and the linkage of words they use in their addresses are value and ideas executive officers pursue. The purpose of this study is to analyze the contents of presidents' addresses introduced in home page of each English literary society in Korea and investigate features and constitution of them each, focusing on analysis of a language network. The results of this study show the features of resemblances and differences of commonly-used words. In addition, these results appear to suggest that they can be also applied to a comparative study between the English literary societies in Korea.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.57-70
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• 1999

Since a hybrid firewall filters packets at a network layer along with providing gateway functionalities at an application layer, it has a better performance than an If filtering firewall. In addition, it provides both the various kinds of access control mechanisms and transparent services to users. However, the security policies of a network layer are different from those of an application layer. Thus, the user interfaces for managing a hybrid firewalls in a consistent manner are needed. In this paper, we implement a graphical user interface to provide access control mechanisms and management facilities for a hybrid firewall such as log analysis, a real-time monitor for network traffics, and the statisics on traffics. And we also propose a new rule script language for specifying access control rules. By using the script language, users can generate the various forma of access control rules which are adapted by the existing firewalls.

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