• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.190-195
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• 2006

The purpose of this study is to suggest the digitalizing model of Belonging relationship information. for this study, the psychological demands of people are analysed based on the premise that the formation of various space is made by mental needs rather than functional needs. The Digitalized Belonging relationship information model consisted of such structuring factors, the visual relationship information, the accessible relationship information and the opening ratios of spaces As a result, the suggested digitalizing model will be considered as an efficient tool for the objective analysis of Belonging relationship between space. In addition, the model will contribute to the expansion of terminology in the field of digital space design

• Korean Institute of Interior Design Journal
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• v.24 no.3
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• pp.146-155
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• 2015

It is an undeniable fact that the modern people's interest in knowledge and information and their roles are some of the core factors used to define the modern society. Besides, as phenomena indicating and leading the modern society, we have fusion, hybrid and convergence, etc. that combine several different elements into a new one. Such changes in social, cultural and technological circumstances require a paradigm shift for the composition of knowledge and information facilities and space. However, more diversified and advanced recently, interfaces for the delivery of knowledge and information cause users to show new behaviors and even change the spatial concept with space composition elements hybridized. Especially for the space of libraries, it is necessary to access and utilize any forms of knowledge and information data (digital + analog) regardless of time and space limitations and approach with an integrated spatial concept likely to change flexibly depending on social demands. In this light, this study aims to make a basic proposal for sustainable integrated-type hybrid space for the space of a public library in this era of knowledge and information. Particularly, this study intends to seek a way to establish a hybrid space model that can effectively converge the most important factors of the space of libraries (human-space(network)-information). With 18 different cases, this study analyzed knowledge and information composition systems, knowledge and information delivery systems and users' space systems. As a result, this study extracted 3 kinds of models, an information-based model, a culture-based model and an education-based model, with the integrated hybrid space model of knowledge and information facilities

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.75-96
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• 1996

This study is intended to compare the effectiveness of the neural network inductive learning model with a vector space model in information retrieval. As a result, searches responding to incomplete queries in the neural network inductive learning model produced a higher precision and recall as compared with searches responding to complete queries in the vector space model. The results show that the hybrid methodology of integrating an inductive learning technique with the neural network model can help solve information retrieval problems that are the results of inconsistent indexing and incomplete queries--problems that have plagued information retrieval effectiveness.

• Journal of Internet Computing and Services
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• v.5 no.2
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• pp.1-15
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• 2004

The current Internet space is evolving to the so called Ubiquitous space. Unlike the Internet space, the information in the Ubiquitous space is distributed evenly in the places like computer's memory, human's brain and physical machine. The 'hypertext', the connection model of the information, which is originally designed for the Internet space doesn't suit well to the Ubiquitous space. From this point of view, we proposed the CPM model in this paper. The CPM model is designed for comprising the such three computing mechanism as analog computing, digital computing and human computing. In this paper, we showed that the characteristics of the CPM model might answer the such purpose as the connection of information in the Ubiquitous space.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.97-104
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• 2016

In this paper, we propose spatial information based simulator for user experience optimization and minimize real space complexity. We focus on developing simulator how to design virtual space model and to implement virtual character using real space data. Especially, we use expanded events-driven inference model for SVM based on machine learning. Our simulator is capable of feature selection by k-fold cross validation method for optimization of data learning. This strategy efficiently throughput of executing inference of user behavior feature by virtual space model. Thus, we aim to develop the user experience optimization system for people to facilitate mapping as the first step toward to daily life data inference. Methodologically, we focus on user behavior and space modeling for implement virtual space.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.107-123
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• 2014

Current text mining techniques suffer from the problem that the conventional text representation models cannot express the semantic or conceptual information for the textual documents written with natural languages. The conventional text models represent the textual documents as bag of words, which include vector space model, Boolean model, statistical model, and tensor space model. These models express documents only with the term literals for indexing and the frequency-based weights for their corresponding terms; that is, they ignore semantical information, sequential order information, and structural information of terms. Most of the text mining techniques have been developed assuming that the given documents are represented as 'bag-of-words' based text models. However, currently, confronting the big data era, a new paradigm of text representation model is required which can analyse huge amounts of textual documents more precisely. Our text model regards the 'concept' as an independent space equated with the 'term' and 'document' spaces used in the vector space model, and it expresses the relatedness among the three spaces. To develop the concept space, we use Wikipedia data, each of which defines a single concept. Consequently, a document collection is represented as a 3-order tensor with semantic information, and then the proposed model is called text cuboid model in our paper. Through experiments using the popular 20NewsGroup document corpus, we prove the superiority of the proposed text model in terms of document clustering and concept clustering.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.500-503
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• 2003

The navigation problem of robot is one of the main themes to deal with conficts or interferences between obstacles and the robot itself In this case, while the robot avoids obstacles on the space, the passage route should be determined efficiently. In order to solve problems above, we have come up with the distance field space medel (DFM) and then, under known environment, we have presented the distance field A algorithm for passage route path search. In this research, the method of performing the 3-dimensional passage route path search of robot under unknown environment is proposed. It is shown that the authors can build the distance search model the does not need space division by taking into account of sensor information to a distance field space model, and constructing this information as virtual obstacle information.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.73-82
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• 2015

Understanding how the topic evolves is an important and challenging task. A topic usually consists of multiple related events, and the accurate identification of event evolution relationship plays an important role in topic evolution analysis. Existing research has used the traditional vector space model to represent the event, which cannot be used to accurately compute the semantic similarity between events. This has led to poor performance in identifying event evolution relationship. This paper suggests constructing a semantic aspect-based vector space model to represent the event: First, use hierarchical Dirichlet process to mine the semantic aspects. Then, construct a semantic aspect-based vector space model according to these aspects. Finally, represent each event as a point and measure the semantic relatedness between events in the space. According to our evaluation experiments, the performance of our proposed technique is promising and significantly outperforms the baseline methods.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.116-121
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• 2020

With the recent development of the 4th Industrial Revolution, efforts have been made to carry out communication in a smart factory, farm, etc. at low cost and reliably. Methods for utilizing empty frequencies using TVWS(TV White Space) have been studied which can be used locally within 30 km. However, there have not been many studies on Path-Loss model considering Korean environment. In this paper, the Path-Loss model is divided into LOS (Line Of Sight) and NLOS (None LOS). In case of LOS model, we checked the difference between Free space model, Friis model, 2-ray model and Hata model with measured data. In the case of NLOS model, we checked the difference between Lee Model, ITU-R526-3 Model with measured data. In order to overcome the difference in Korean environment, we derived a model that can be applied in LOS and NLOS and prove its usefulness through performance evaluation through simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.