• Journal of Digital Contents Society
• /
• v.5 no.1
• /
• pp.7-11
• /
• 2004

There are many problems that must solve to construct next generation high-speed communication network. Among these, item that must consider basically is characteristics analysis of traffic that nows to network Traffic characteristics of many Internet services that is offered present have shown that network traffic exhibits at a wide range of scals-self-similarity. Self-similarity is expressed by long term dependency, this is contradictory concept with Poisson model that have relativity short term dependency. Therefore, first of all, for design and dimensioning of next generation communication network, traffic model that are reflected burstiness and self-similarity is required. Here self-similarity can be characterized by Hurst parameter. In this paper, the calculation equation is derived considering queueing delay and self-similarity of data traffic art compared with simulation results.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.113-124
• /
• 2021

The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.

• Journal of KIISE:Software and Applications
• /
• v.26 no.1
• /
• pp.167-167
• /
• 1999

The majority of text categorization systems use the term-based classification method. However, because of too many terms, this method is not effective to classify the documents in areal-time environment. This paper presents a real-time concept-based text categorization system,which classifies texts using thesaurus. The system consists of a Korean morphological analyzer, athesaurus tool, and a probability-vector similarity measurer. The thesaurus tool acquires the meaningsof input terms and represents the text with not the term-vector but the concept-vector. Because theconcept-vector consists of semantic units with the small size, it makes the system enable to analyzethe text with real-time. As representing the meanings of the text, the vector supports theconcept-based classification. The probability-vector similarity measurer decides the subject of the textby calculating the vector similarity between the input text and each subject. In the experimentalresults, we show that the proposed system can effectively analyze texts with real-time and do aconcept-based classification. Moreover, the experiment informs that we must expand the thesaurustool for the better system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.11 no.4
• /
• pp.238-246
• /
• 2011

This paper proposes a new semantic representation and its associated similarity measure. The representation expresses textual context observed in a context of a certain term as a network where nodes are terms and edges are the number of cooccurrences between connected terms. To compare terms represented in networks, a graph kernel is adopted as a similarity measure. The proposed representation has two notable merits compared with previous semantic representations. First, it can process polysemous words in a better way than a vector representation. A network of a polysemous term is regarded as a combination of sub-networks that represent senses and the appropriate sub-network is identified by context before compared by the kernel. Second, the representation permits not only words but also senses or contexts to be represented directly from corresponding set of terms. The validity of the representation and its similarity measure is evaluated with two tasks: synonym test and unsupervised word sense disambiguation. The method performed well and could compete with the state-of-the-art unsupervised methods.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.4
• /
• pp.76-83
• /
• 2020

Postal logistics organizations are characterized as having high labor intensity and short response times. These characteristics, along with rapid change in mail volume, make load scheduling a fundamental concern. Load analysis of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations is required for optimal postal logistics operation. In particular, the performance of mail traffic forecasting is essential for optimizing the resource operation by accurate load analysis. This paper addresses a traffic forecast problem of postal parcel that arises at delivery stations of Korea Post. The main purpose of this paper is to describe a method for predicting short-term traffic of postal parcel based on self-similarity analysis and to introduce an application of the traffic prediction model to postal logistics system. The proposed scheme develops multiple regression models by the clusters resulted from feature engineering and individual models for delivery stations to reinforce prediction accuracy. The experiment with data supplied by main postal delivery stations shows the advantage in terms of prediction performance. Comparing with other technique, experimental results show that the proposed method improves the accuracy up to 45.8%.

• Journal of Korea Technology Innovation Society
• /
• v.8 no.spc1
• /
• pp.360-390
• /
• 2005

The paradigm of the corporate innovations has been changed from the intra-company innovations to the inter-company innovations. A prevalent approach to the inter-company innovations is the supply chain management. Three key words of the core concept of supply chain management are the long-term relationship, resource integration, and value creation. Specifically, it means that the supply chain management aims to make value creation through the resource integration for the supply chain entities, based on the long-term relationship between buyers and sellers. To make more effective long-term relationship among the supply chain entities, it is very important for the supply chain entities to analyze followings: i) What variables can influence the long-term relationship, ii) How these variables can influence to the long-term relationship. However, previous researches mostly deals the long-term relationship in the marketing area in fragment, and thus few research efforts have been done for the development of conceptual model using supply chain management theories. In contrast to previous studies, our research tried to develop and examine the integrative research model by introducing both the marketing theories and the supply chain management theories, and thus related hypotheses are derived. A multiple regression analysis was performed to examine the influence of the antecedents of the long-term relationship, for the 87 retailers of grocery supply chains. The empirical results confirm that cultural similarity, reputation, interdependency, and trust positively influence long-term relationship (i.e., partnership orientation and partnership symmetry). And results also confirm that the supply implementation factors such as organization integration, information system integration, and process integration playa moderating role between antecedents and long-term relationship. These findings suggest that companies should perceive the importance of managing the process, organization, information system integration in the long-term relationship implementation process as well as the factors such as cultural similarity, reputation, interdependency, and trust in the long-term relationship establishment process.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.1
• /
• pp.99-105
• /
• 2011

We propose a semi-supervised learning algorithm based on a form of regularization that incorporates similarity and dissimilarity penalty terms. Our approach uses a graph-based encoding of similarity and dissimilarity. We also present a model-selection method which employs cross-validation techniques to choose hyperparameters which affect the performance of the proposed method. Simulations using two types of dat sets demonstrate that the proposed method is promising.

• Journal of the Korean Professional Engineers Association
• /
• v.38 no.2
• /
• pp.60-63
• /
• 2005

Firstly, the author suggests a new term of the "Pro-Engineer's Doctrine" on every engineering work. This renewed term should be in their minds who are doing any kinds of scientific and technological works in his/her field. The term, "doctrine", is based on a wise sage, renewedly, so-called "The Way of the measuring squire(혈矩之道)" saying in one of the Oriental classics. Also, he explains here another term, "Investigation of things, attainment of knowledge(格物致知)" that is very similarity to the "Pro-Engineer's Doctrine" from the same book.

• Journal of the Korean Society for information Management
• /
• v.23 no.3 s.61
• /
• pp.147-165
• /
• 2006

In this study, experiments for selection of association terms were conducted in order to discover the optimum method in selecting additional terms that are related to an initial query term. Association term sets were generated by using support, confidence, and lift measures of the Apriori algorithm, and also by using the similarity measures such as GSS, Jaccard coefficient, cosine coefficient, and Sokal & Sneath 5, and mutual information. In performance evaluation of term selection methods, precision of association terms as well as the overlap ratio of association terms and relevant documents' indexing terms were used. It was found that Apriori algorithm and GSS achieved the highest level of performances.

• Journal of KIISE:Software and Applications
• /
• v.29 no.4
• /
• pp.258-269
• /
• 2002

There have been many studies of automatic term recognition (ATR) and they have achieved good results. However, there are scopes to improve the performance of extracting terms still further by using the additional technical dictionaries. This paper focuses on the method for extracting terms using the hierarchy among technical dictionaries. Moreover, a statistical method based on frequencies, foreign words, and nested relations assists extracting terms which do not appear in dictionaries. Our method produces relatively good results for this task.