• Lingua Humanitatis
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• v.2 no.1
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• pp.75-92
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• 2002

The historical facts usually remain in the linguistic records. The name of a place has been considered most useful among the records. The name of a place contains lots of information which help us analyzing and explaining the historical problems. The main purpose of this thesis is to account for the relation between language and history based on the data of the name of a place with the property just mentioned above. Firstly I will estimate the territory of the former period of Paek-Che (18B.C.~475A.D.) on the basis of the distribution of the old name of a place and show that the presumed shape of the territory could prove the fact that the unification of Shilla is 'the unification of two nations' but not 'the unification of three nations' Secondly the distribution of the old name of a place can bring light on the interrelation between Paek-Che language and Kara language and help us understand the relation of neighboring countries between two nations. Thirdly we can discuss the relation between the language of the former period of Paek-Che and of the old period of Japan: that is, how the language of Paek-Che came in the Japanese language. Also, the history of cultural domination between Paek-Che and Japan could be clarified if we can prove the linguistic similarity of two nations either to be genealogical relation or to be borrowing one.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1099-1109
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• 1995

By using a concept of interrelation quadruplet between line segments, a new method for recognition of object families is introduced. The interrelation quadruplet, which is invariant under similarity transform of a pair of line segments, is used as a feature information for polygonal shape recognition. Several useful propertes of the interrelation quadruplet are derived in relation to efficient recognition of object families. Compared with the previous methods, the proposed method requires only small space of storage and is shown to be computationally simple and efficient.

• Science of Emotion and Sensibility
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• v.18 no.4
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• pp.35-46
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• 2015

Prior research suggested that people generally show stronger intentions to help in-group members because people experience higher levels of empathy for those who are similar to themselves. The present research demonstrated that one's levels of cosmopolitanism would moderate the mediating role of empathy on the relationship between cultural similarities and helping intentions. In particular, it was examined how the mediator (empathy) affected the relation between cultural similarity and helping intention for participants with low to high levels of cosmopolitanism. Results indicated that participants with lower levels of cosmopolitanism showed stronger empathy as targets are more culturally similar to participants' own culture. Participants with higher levels of cosmopolitanism, however, reported the same levels of empathy regardless of targets' cultural similarity. The implications and limitations of the results were discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.224-229
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• 2011

Collaborative filtering is used the most for recommendation systems because it can recommend potential items. However, when there are not many items to be evaluated, collaborative filtering can be subject to the influence of similarity or preference depending on the situation or the whim of the evaluator. In addition, by recommending items only on the basis of similarity with items that have been evaluated previously without relation to the present situation of the user, the recommendations become less accurate. In this paper, in order to solve the above problems, before starting the collaborative filtering procedure, we calculated similarity not by comparing all the values evaluated by users but rather by comparing only those users who were above the average in order to improve the accuracy of the recommendations. In addition, in the ceaselessly changing ubiquitous computing environment, it is not proper to recommend service information based only on the items evaluated by users. Therefore, we used methods of calculating similarity wherein the users' real time context information was used and a high weight was assigned to similar users. Such methods improved the recommendation accuracy by 16.2% on average.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.43-66
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• 2008

Currently be proceeded a lot of researchers for 'user information demand description' for interface of an information retrieval system or Web search engines, but user information demand description for a natural language form is a difficult situation. These reasons are as they cannot provide the semantic similarity that an information retrieval model can be completely satisfied with variety regarding an information demand expression and semantic relevance for user information description. Therefore, this study using the description logic that is a knowledge representation base of OWL and a vector model-based weight between concept, and to be able to satisfy variety regarding an information demand expression and semantic relevance proposes a decision way for perfect assistances of user information demand description. The experiment results by proposed method, semantic similarity of a polyseme and a synonym showed with excellent performance in decision.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.65-72
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• 2014

Change coupling is a measure to show how strongly change-related two entities are. When two source files have been frequently changed together, they are regarded as change-coupled files and they will probably be changed together in the near future. In the previous studies, the change coupling between two files is defined with the number of common changed time, that is, common commit time of the files. However, the frequency-based technique has limitations because of 'tangled changes', which frequently happens in the development environments with version control systems. The tangled change means that several code hunks have been changed at the same time, though they have no relation with each other. In this paper, the change types of the code hunks are also used to define change coupling, in addition to the common commit time of target files. First, the frequency vector based on change types are defined with the extracted change types, and then, the similarity of change patterns are calculated using the cosine similarity measure. We conducted experiments on open source project Eclipse JDT and CDT for case studies. The result shows that the applicability of the proposed method, compared to the previous studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.340-342
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• 2004

In this paper, we introduce a new category of fuzzy inference systems baled on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of information with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.1-5
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• 2003

In an early paper Skumanich suggested the existence of a scaling law relating the mean sunspot magnetic field with the square-root of the photospheric pressure. This was derived from an analysis of a variety of theoretical spot models including those by Yun (1968). These were based on the Schliiter-Temesvary (S- T) similarity assumption. To answer criticisms that such modeling may have unphysical (non-axial maxima) solutions, the S-T model was revisited, Moon et al. (1998), with an improved vector potential function. We consider here the consequences of this work for the scaling relation. We show that by dimensionalizing the lateral force balance equation for the S- T model one finds that a single parameter enters as a characteristic value of the solution. This parameter yields Skumanich's scaling directly. Using an observed universal flux-radius relation for dark solar magnetic features (spots and pores) for comparison, we find good to fair agreement with Yun's characteristic value, however the Moon et al. values deviate significantly.