• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.32-35
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• 2008

본 논문은 포털 사이트의 효율적인 광고 제공을 위한 자연어처리 기반의 키워드 광고 시스템을 제안한다. 사용자의 질의에 대한 형태소 분석 결과를 사용하여, 기존의 키워드 정합에 의한 광고 시스템보다 재현율을 향상시킬 수 있었다. 또한, 웹 기반 키워드 광고 뿐 아니라 메신저를 통한 대화 내용 기반 키워드 광고도 제안한다.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1113-1120
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• 2004

This paper proposes a novel hybrid genetic algorithm for the feature selection. Local search operations are devised and embedded in hybrid GAs to fine-tune the search. The operations are parameterized in terms of the fine-tuning power, and their effectiveness and timing requirement are analyzed and compared. Experimentations performed with various standard datasets revealed that the proposed hybrid GA is superior to a simple GA and sequential search algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.3
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• pp.119-124
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• 2014

Let G = (V, E) be a graph. Maximum Bipartite Subgraph Problem is to convert a graph G into a bipartite graph by removing minimum number of edges. This problem belongs to NP-complete; hence, in this research, we are suggesting a new metaheuristic algorithm which combines Tabu search and GRASP.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1112-1120
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• 1996

One of different methods to increase the productivity of software development team is to reuse the software components which were used once. Such a reusable software components are often organized software libraries. In order to reuse effectively the software modules selected from a library, the users need information enough to search for the modules easily. This paper designs and implements the tool which provides the information about the relationship between classes to reuse software components, and makes a new class by combining the data and functions from existing classes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.195-204
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• 2020

Nowadays there are over 1.6 billion web pages and it is hard to get necessary results that user wants. Most search engines allow you to search with logical form to get accurate results. However, normal users are not familiar to search information as logical form. Therefore, they search in natural language rather than in complicated logical form. In this paper there are some suggestions to improve quality of searching results, converting natural language input by the user into logical form which can able to use advanced search engine. Users tend to make short searches due to the 'Simplicity' which is one of the features of the search form. Therefore we suggest history retrieval method; advanced version of previous suggestion to provide convenience to the normal users. We had improvement on accuracy of the search results converting natural languages to logical form and also can contain every keyword without missing any keywords using searching methods on this paper. It is expected that these search methods will contribute to the development of search engines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.816-822
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• 2016

Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.29-30
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• 2019

본 논문에서는 다중 컨트롤러가 존재하는 분산 SDN 환경에서 과도한 제어 메시지로 인한 과부하된 컨트롤러의 부하를 줄이기 위하여 이주할 스위치를 K-means 군집화와 Harmony Search(HS)를 기반으로 선정 하는 기법을 제안하였다. 기존에 HS를 이용하여 이주할 스위치를 선택하는 기법이 제시되었으나, 시간 소모에 비하여 정확도가 부족한 단점이 있다. 또한 Harmony Memory(HM) 구축을 위해 메모리 소모 또한 크다. 이를 해결하기 위하여 본 논문에서는 유클리드 거리를 기반으로 하는 K-means 군집화를 이용하여 이주할 스위치를 골라내어 HM의 크기를 줄이고 이주 효율을 향상 시킨다.