• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.1-7
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• 2019

Program similarity analysis consists of substantial similarity and access. Substantial similarity is a judgment of how similarly the program source code is quantitatively. Access determines the degree of similarity by analyzing comments in the program or other contextual evidence. In the case of manuals, it may be the subject of legitimacy analysis. Manuals can be divided into three types as follows. First, a master manual is a document created during the development stage of a product. It is a user manual that contains all the functionality of the product and its derivatives. Second, the customer manual is a manual that is open only to the primary customer and orderer. Third, the user manual is a document that is applied to the final OEM production stage and is open to the end purchaser. In this paper, we compare the master manual seized from the suspect and the master manual provided by the suspect on the Internet. It then determines how similar this master manual is and includes the victim company's original and property values.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.511-516
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• 2012

In this paper, we investigate $h$-stability of the nonlinear perturbed differential systems using the the notion of $t_{\infty}$-similarity.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1324-1329
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• 2004

In this article we have tested stability of classifier based on fuzzy similarity in generalized Lukasiewicz structure. Two different tests for stability was made:In on test stability was checked respect to weight parameters and other test was carried out for idealvectors. Tests have made with three different classification problems.

• Korean Journal of Mathematics
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• v.23 no.2
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• pp.269-282
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• 2015

In this paper, we investigate bounds for solutions of perturbed functional differential systems using the notion of $t_{\infty}$-similarity.

• The Pure and Applied Mathematics
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• v.22 no.3
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• pp.215-227
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• 2015

In this paper, we investigate bounds for solutions of nonlinear functional differential systems using the notion of t_∞-similarity.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.4
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• pp.695-702
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• 2011

In this paper, we investigate h-stability of the non-linear perturbed differential systems using the the notion of $t_{\infty}$-similarity.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.2
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• pp.393-400
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• 2011

In this paper we study h-stability for the linear impulsive equations using the notion of kinematical similarity and impulsive integral inequality.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.585-588
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• 2008

This paper proposes hand gesture recognition using shape similarity method. For this, we require two steps which are aquisition of Hand area and similarity evaluation. First step is extracting hand area using YCbCr color spare. Then eliminate noise through filter and analyzing histogram. For doing this, we ran measure similarity of hand gesture by applying TSR after getting contour. Finally, we utilize shape similarity for recognizing of hand gesture.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1311-1314
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• 2003

In this paper, we propose a method to measure document similarity. First, we have exploited single-term method that extracts nouns by using a lexical analyzer as a preprocessing step to match one index to one noun. In spite of irrelevance between documents, possibility of increasing document similarity is high with this method. For this reason, a term-phrase method has been reported. This method constructs co-occurrence between two words as an index to measure document similarity. In this paper, we tried another method that combine these two methods to compensate the problems in these two methods. Six types of features are extracted from two input documents, and they are fed into a neural network to calculate the final value of document similarity. Reliability of our method has been proved by an experiment of document retrieval.