• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.117-120
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• 2002

In this paper, we propose a new text watermarking method using space coding and PN sequence. A PN sequence generated from user message modifies the space between words in each line. The detection can be done without original text image using the average space with in the text. Experimental results show that proposed method has the invisible property and robustness to the attack such as the elimination of words in the text.

• Korean Institute of Interior Design Journal
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• v.16 no.4
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• pp.31-38
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• 2007

This study is interested in how philological interpretation of a space text were patterned so as to give the text structural cohesion. A similar philological motivation incorporates some of the notions of generative grammar. Interpretation is the process of recovering the cultural meanings expressed in discourse by analysing the linguistic structures in the light of their interactional and wider social contexts. Viewed in this light, the process of this study is illustrated as follows: At first, this research contains basic concepts of signification of text and context, and theories of spacial text and context of typological structure in terms of Ricoeur's structural Hermeneutics. Secondly, it concretize a logic that traditional space context is inserted in organized attribute like emotion, spirit, nature as character of contemporary space text through typological structure. Finally, from aspect of designation theory among interpretive semantics, it shows that korean contemporary space design is incorporated with typological structure of korean traditional palace spacial context homologically through the case study of I-Hotel space design. Through this process, this study suggest that positivistic interpretation methodology by designation of text is logical thinking of Korean traditional space design.

• Journal of the Korean housing association
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• v.25 no.6
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• pp.101-109
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• 2014

It was early in the $20^{th}$ century when the space was begun to say through the mutual circumstances of form and contents. Adrian Forty explained that the characteristics of space can be divided into three steps by the period: a space of enclosure, a space as continuum and a space as an extension of the body. And there is common condition that all three spaces are accompanied by the form. In the new thinking of architectural form in terms of text in modern society, architecture becomes to more complex to understanding. Saying that there is nothing outside text (Il n'y a rien en dehors du text.) in the world, Jacques Derrida insisted the world to be texted and not to be special centrality, where can be existed by difference and delay its meaning. Text is the structural meaning (sign), not a metaphorical one (symbol). Without the symbol, the architecture can be recognized as text with signing to the form. For that, there is a question how can be explained the space in terms of text extracting the meaning and the symbol. Absolutely not intended by Mies van der Rohe, but in his works of houses and pavilion, its characteristics and traces of text can be seen. If it is possible to analyse his works in the textual view, space of Mies will be found in the same direction of text. And it will be an important opportunity to re-evaluate the space of Mies works standing in the heart of Modern Architecture.

• 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.

• Smart Media Journal
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• v.2 no.1
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

• Archives of design research
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• v.14 no.4
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• pp.199-207
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• 2001

The public performance of drama has essence to convert text to visual images as stage and to represent, inform such visual images. Visual image is formed through a space as stage. Stage is a dish to fill the texts and is the mother's womb of visual image. Namely, visual image of drama equals space image. The purpose of this study is a trial to grasp the structure and system represented through interpreting. Especially, the concerns of this study are not semiology of letter imported in image but spacial image text importing just contents of text and the process and contents grasping the structure and meaning of dramatic space. Finally, this study proposed 'the system of space embodiment'from the semiotic point of view as interpretation methodology of actual memorial, symbolic space.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1397-1409
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• 2017

For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.5-10
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• 2009

Text data has always accounted for a major portion of the world's information. As the volume of information increases exponentially, the portion of text data also increases significantly. Text classification is therefore still an important area of research. LDA is an updated, probabilistic model which has been used in many applications in many other fields. As regards text data, LDA also has many applications, which has been applied various enhancements. However, it seems that no applications take care of the input for LDA. In this paper, we suggest a way to map the input space to a reduced space, which may avoid the unreliability, ambiguity and redundancy of individual terms as descriptors. The purpose of this paper is to show that LDA can be perfectly performed in a "clean and clear" space. Experiments are conducted on 20 News Groups data sets. The results show that the proposed method can boost the classification results when the appropriate choice of rank of the reduced space is determined.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.1-8
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• 1996

This paper presents a text-driven discourse analysis system, called DPAS. DPAS constructs a discourse structure by weaving together clauses in the text by finding discourse relations between a clause and the clauses in a context. The basic processing model of DPAS is based on the stack based model of discourse analysis suggested by Grosz and Sidner. We extend the model with dynamic programming method to handle various discourse ambiguities effectively and efficiently. We develop the idea of a context space to keep all information of a context. DPAS parses a text by considering all possible discourse relations between a clause and a context. Since different discourse relations may result in different states of a context, DPAS maintains multiple context spaces for an ambiguous text. Since maintaining all interpretations until the whole text is processed requires too much computing resources, DPAS uses the idea of depth-limited search to limit the search space. If there is more than one discourse relation between an input clause and a context, DPAS constructs context spaces one context space for each discourse relation. Then, DPAS applies heuristics to choose the most desirable context space after it processes some more input clauses. Since the basic idea of DPAS is domain independent, although we used descriptive texts to demonstrate DPAS, we believe the idea of DPAS can be extended to understand other styles of texts.

• Korean Institute of Interior Design Journal
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• v.15 no.4 s.57
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• pp.64-72
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• 2006

The purpose of this study is to interpret Korean traditional space as text on the basis of Structuralism. The process of this study is illustrated as follows: At first, this research contains basic concepts and theories of Structuralism and discusses the possibilities of typological approaches in Korean traditional space interpretation. Secondly, As typological structure of traditional space, spacial and visual expressive characteristics in traditional residential space based on traditional thoughts of Koreans formed with inherent consciousness are considered with Hjelmslev's Structuralism and Wonhyo's Whajaeng theory. Finally, This study tries conceptual analysis based on Lacan's Metaphor and Metonymy emerged from unconscious mechanisms about interpretation and induction of the traditional spacial structure for contemporary Application. Structure is a group of elements forming a covariant ensemble. From this point of view, this study validates that texts are understood when methods that bring back to the creative processes and intentions are found by Text Hermeneutics.