• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.1-9
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• 2010

In the new generation of Web, commonly called "Web 2.0", blogging has facilitated the publishing information or his/her opinion on the web. Various blog retrieval algorithms have been proposed to search for blogs more effectively. However, actually keyword-based searching or link-analysis blog ranking system cannot satisfy the user's requirement. In this paper, we suggest a topic-based weighting blog retrieval system in which the links between blog writings and searching words are considered to improve the search results. Our system extracts topics from each blog and weights them much higher than other guide words. In the comparison with other systems, we see that the proposed topic-base system has better recall rate of search results.

• Journal of KIISE
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• v.41 no.9
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• pp.652-665
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• 2014

Many important terminologies in biomedical text are expressed as abbreviations or acronyms. We newly suggest a semantic link topic model based on the concepts of topic and dependency link to disambiguate biomedical abbreviations and cluster long form variants of abbreviations which refer to the same senses. This model is a generative model inspired by the latent Dirichlet allocation (LDA) topic model, in which each document is viewed as a mixture of topics, with each topic characterized by a distribution over words. Thus, words of a document are generated from a hidden topic structure of a document and the topic structure is inferred from observable word sequences of document collections. In this study, we allow two distinct word generation to incorporate semantic dependencies between words, particularly between expansions (long forms) of abbreviations and their sentential co-occurring words. Besides topic information, the semantic dependency between words is defined as a link and a new random parameter for the link presence is assigned to each word. As a result, the most probable expansions with respect to abbreviations of a given abstract are decided by word-topic distribution, document-topic distribution, and word-link distribution estimated from document collection though the semantic dependency link topic model. The abstracts retrieved from the MEDLINE Entrez interface by the query relating 22 abbreviations and their 186 expansions were used as a data set. The link topic model correctly predicted expansions of abbreviations with the accuracy of 98.30%.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.72-80
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• 2021

Metaverse is an immersive 3D virtual environment, a true virtual artificial community in which avatars act as the user's alter ego and interact with each other. If we do not manage the hype for the metaverse, which has recently been receiving a surge in interest, the metaverse will fail to cross the chasm. In this study, to provide stakeholders with insights for the successful introduction and growth of the 3D immersive next-generation virtual world, metaverse, we analyzed user-side interest, media-side interest, and research-side interest. For this purpose, in this study, search traffic, news frequency and topic, and research article frequency and topic were analyzed. The methodology and results of this study are expected to provide insight for the stable success of metaverse transformation and the coexistence of the real world and the virtual world through hyper-connection and hyper-convergence.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.93-96
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• 2017

DDS (Data Distribution Serivce) communication middleware is spreading to various private sector as well as the defense sector because it can obtain a very high application effect in a complex system environment in which a plurality of data producers and data consumers are connected by a network. However, application development using DDS middleware is an inefficient structure with a lot of repetitive codes because most users perform 1: 1 mapping with the message they want to exchange. Accordingly, the user has to perform unnecessary repetitive tasks as the topic increases. Therefore, a development support tool that identifies a series of processes required for using DDS middleware and automatically generates the classes that are repeated by Topic is required. In this paper, we propose a method for DDS communication by automatically generating a common class for efficient use of DDS middleware.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.1-13
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• 2004

The Semantic Web introduces the next generation of the Web by establishing a semantic layer of machine-understandable data to enable machines (i.e intelligent agents) retrieve more relevant information and execute automated web services using semantic information. Ontology-related technologies are very important to evolve the World Wide Web of today into the Semantic Web in representation and share of semantic data. In this paper, we proposed and implemented the efficient ontology management system, K-Box, which constructs and manages ontologies using topic maps. We can use K-Box system to construct, store and retrieve ontologies. K-Box system has several components: Topicmap Factory, Topicmap Provider, Topicmap Query Processor, Topicmap Object Wrapper, Topicmap Cache Manager, Topicmap Storage Wrapper.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.525-528
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• 2007

기존의 웹서비스가 정적이고 수동적인데 반해 최근의 웹 서비스는 점차 동적이고 능동적으로 변화하고 있다. 이러한 웹서비스 변화의 흐름을 잘 반영하는 것이 웹 2.0이다. 웹 2.0에서 대부분의 정보는 사용자에 의해 생산되고, 사용자가 붙인 태그(tag)에 의해 분류되어진다. 그러나 현재 태그에 관한 서비스 및 연구들은 태깅(tagging) 방법에 대한 연구를 비롯해 이를 표현하기 위한 tag cloud에 초점이 맞춰져 진행됨에 따라, 다양한 태그 정보자원 간의 체계와 연결 관계인 지식체계를 제공하지 못하고 있다. 이에 본 논문에서는 체계화된 지식표현을 위해 웹상에 편재되어 있는 학습 관련 리소스(resources) 및 태그들를 수집한다. 이를 사용자가 요청한 검색 키워드와 연관성이 있는 태그 정보들을 맵핑 및 클러스터링하여 최적화된 표현 형식인 토픽 맵(topic map)화하기 위한 시스템을 제안하며, 이 중 토픽 맵 생성을 위한 초기 연구 단계로서, 연관 태그들 간의 맵핑 및 클러스터링을 위한 알고리즘 제시를 중심으로 소개한다.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Korean Management Science Review
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• v.18 no.1
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• pp.155-164
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• 2001

The widespread diffusion of Internet has enables every college and education institute to develope cyber education systems to meet the multiple needs of students, but it is not true that the effectiveness of cyber education is fruitful in terms of evaluation systems. Most of the early developed web-based evaluation systems for cyber education require that all the students should solve uniformed test set which are included in the predetermined static HTML pages. Therefore, it is impossible to dynamically provide a test set with consistency and reliability. This paper purpose to describe the employment of simulated annealing in cyber testbank system for test set generation that satisfy all constraints. The constraints include number of items for each skill, method, domain, topic, and so on. This research developed two phase heuristic combining sequential test set generation algorithm with simulated annealing. As a result of computer simulations, it was found that the two phase heuristic outperforms the other algorithms.

• Language and Information
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• v.16 no.1
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• pp.1-24
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• 2012

-Nun is generally known as a Topic marker in Korean. However, when it is combined with an accent, it is thought to have a different function, which is alleged to indicate 'contrast' (Kuno 1972). Although the fact that -nun marked item generates some kind of 'contrastive meaning' is uncontroversial, what 'contrast(ive)' means is still unclear. In t his paper, I propose that accented -nun generates two types of implicit propositions in addition to its at-issue meaning. A simple sentence has been repeatedly tested in various models in order to see what type of proposition each proposition corresponds to and it has been concluded that one is presupposition and the other is implicature. This tedious-looking test forms the main part of the first-half of this paper. The presupposition is the essential factor for the -nun marked item to obtain the 'contrastive' meaning. Based on the generation of this presupposition, I argue that -nun works as a contrast operator in a sentence. To illustrate -nun's function as a contrast operator forms the latter part of this paper.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.547-551
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• 1995

We analyze the nonlinearity of chiral media and coupled-mode theory of chiral multilayers. In first topic, second order nonlinear coupled equations are constructed and a phase matchine method is suggested. This approach can be developed to higher order nonlinearity and electric-field-induced second harmonic generation. In second topic, coupled mode equation in chiral multilayers is constructed, and solved for both codirectional coupling and contradirectional coupling. There is a previous formulation about chiral mutilayers[1] with 4$\times$4 matrix but it did not give detail results, so this approach will be compared with that.