• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.11-18
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• 2019

Previous mutual authentication schemes operate on the basis of validated cryptographic functions and hash functions, but these functions require a certain amount of memory capacity. However, since ultra-lightweight IoT devices have a very small amount of memory capacity, these functions can not be applied. In this paper, we first propose a text steganography communication scheme suitable for ultra-lightweight IoT devices with limited resources, and then propose a mutual authentication scheme based on the text steganography communication. The proposed scheme performs mutual authentication and integrity verification using very small amount of memory. For evaluation, we implemented the proposed scheme on Arduino boards and confirmed that the proposed scheme performs well the mutual authentication and the integrity verification functions.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.241-246
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• 2013

A classic document clustering technique may incorrectly classify documents into different clusters when documents that should belong to the same cluster do not have any shared terms. Recently, to overcome this problem, internal and external knowledge-based approaches have been used for text document clustering. However, the clustering results of these approaches are influenced by the inherent structure and the topical composition of the documents. Further, the organization of knowledge into an ontology is expensive. In this paper, we propose a new enhanced text document clustering method using non-negative matrix factorization (NMF) and WordNet. The semantic terms extracted as cluster labels by NMF can represent the inherent structure of a document cluster well. The proposed method can also improve the quality of document clustering that uses cluster labels and term weights based on term mutual information of WordNet. The experimental results demonstrate that the proposed method achieves better performance than the other text clustering methods.

• Journal of KIISE
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• v.44 no.11
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• pp.1236-1243
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• 2017

In this paper, we propose a novel way of producing keyword networks, named LSI-based ClusterTextRank, which extracts significant key words from a set of clusters with a mutual information metric, and constructs an association network using latent semantic indexing (LSI). The proposed method reduces the dimension of documents through LSI, decomposes documents into multiple clusters through k-means clustering, and expresses the words within each cluster as a maximal spanning tree graph. The significant key words are identified by evaluating their mutual information within clusters. Then, the method calculates the similarities between the extracted key words using the term-concept matrix, and the results are represented as a keyword association network. To evaluate the performance of the proposed method, we used travel-related blog data and showed that the proposed method outperforms the existing TextRank algorithm by about 14% in terms of accuracy.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.984-990
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• 2007

As the amount of electronic documents increases explosively, automatic text categorization methods are needed to identify those of interest. Most methods use machine learning techniques based on a word set. This paper introduces a new method, called FPTC (FP-Tree based Text Classifier). FP-Tree is a data structure used in data-mining. In this paper, a method of storing text sentence patterns in the FP-Tree structure and classifying text using the patterns is presented. In the experiments conducted, we use our algorithm with a #Mutual Information and Entropy# approach to improve performance. We also present an analysis of the algorithm via an ordinary differential categorization method.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.933-937
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• 2009

Interactive multi-media advertising is a new field with broad space of research coming into being with the emergence and extensive application of computer multi-media technology. This text analyzes the existing application in the advertisement of mutual media at first. Secondly analyze the public service advertisement design in the mutual media and public space. Through to in the public space, utilize to public service advertisement design and analysis of the mutual media, To characteristic and advantage of the mutual media, make the application of the public service advertisement to carry on research on the public space.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.1-7
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• 2024

Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.105-110
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• 2005

Painting and writing are exceedingly different in the way they are visually express. However, if one were to trace the roots of both painting and writing, one would discover the two have the same origins. At one time, both painting and writing fulfilled the function portraying mutual or reciprocal messages to the masses. On the other hand, after the time of medieval manuscript and typography, they were separated completely into image and text. Today, the images are interpreted into the text. Meanwhile, the text better communicates its ideas to the masses through additional support of the simultaneous image. The joint use of the shaping of mutual exchanges between literature and visual art is being enlivened between scholars through their tendency to converse or communicate through the media. Moreover, the visual configuration and characters that strike into the new media are one of the various uses and the significantly important methods of deliberative communication that are necessary for hypertext functioning. In the following text, I will expande and develope the historical communication scheme and the process of modification of painting and writing, lead the origination of modern new-pictograph.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.259-267
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• 2003

Though naive Bayes text classifiers are widely used because of its simplicity, the techniques for improving performances of these classifiers have been rarely studied. In this paper, we propose and evaluate some general and effective techniques for improving performance of the naive Bayes text classifier. We suggest document model based parameter estimation and document length normalization to alleviate the Problems in the traditional multinomial approach for text classification. In addition, Mutual-Information-weighted naive Bayes text classifier is proposed to increase the effect of highly informative words. Our techniques are evaluated on the Reuters21578 and 20 Newsgroups collections, and significant improvements are obtained over the existing multinomial naive Bayes approach.

• 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.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.160-168
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• 2007

For developing a text classifier using supervised learning, a manually labeled corpus of large size is required. However, it takes a lot of time and human effort. Recently a research paradigm was proposed to use a raw corpus and a small amount of seed information instead of manually labeled corpus. In this paper we introduce an unsupervised learning method that makes it possible to achieve better performance than other related works. The characteristics of our approach is that average mutual information is used to learn representative words and their weights and then update of the weights is done using a technique inspired by the works in information retrieval. By iterating this teaming process it was shown that a high performance system can be developed.