• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.405-416
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• 2008

To overcome the limitation of keyword-based integrated search, this study shows entity-centric integrated search method using URI scheme. Our system generates entity pages in ways of analyzing user's keyword and instances matched with it, selecting optimal entity type, and calling unit services simultaneously. Topic information extracted from articles is propagated to persons, institutions, and locations by reasoning for providing topic-centric information. With comparative experiments based on search results and usability tests, we proved that this approach is superior to keyword-based integrated search served by CiteSeer and Google Scholar.

• Plant Journal
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• v.8 no.1
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• pp.50-59
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• 2012

The current dual-watchdog estimation system has individually calculated the construction, the engineering and the procurement cost. The dual-watchdog estimation system is inefficient and prolonged estimation period because of the lack of the interoperability and the difference of material unit cost and construction unit cost. In order to resolve this problem, new estimation software was developed. The estimation software is developed by making up for the weak points in existing estimation method. The cost data with the same standard is the key point. And this software enhanced accuracy and speed of the data search in stylized estimation standard. A summary of the construction, the engineering and the procurement cost was generated in this estimation software. The unit rate about the labor cost, equipment and expense through a sheet was handled. The developed estimation software has five categories on engineering cost, procurement cost, construction cost and subcontractor management sheet. In this study, the estimation software to supplement the faults of the existing estimation method was developed. And estimation software on petrochemical projects increases an efficiency of the estimation work.

• Journal of Community Nutrition
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• v.7 no.3
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• pp.149-155
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• 2005

This exploratory study investigated the software programs utilized by clinical dietitians and their perceptions on the use of information technology. The study focused on the use of specialized software for dietetics, general software for any office use and the Internet. A self-administered survey was used to collect data from clinical dietitians identified in the Kentucky Dietetic Association Directory 2003-2004. The survey was conducted in March through April, 2004. A total of 22 responses were collected, which yielded a response rate of $68\%$. Findings suggest that computer use has become a routine for optimal clinical practice ; major specialized software programs are used for nutrition assessment, nutrition analysis and menu development. Use of specialized software appears to be unassociated with dietitians' age and years of experience ; however, the associations are indicated between use of specialized software and education level as well as their specialty ; word processing and spreadsheet are the major general software used. Internet is used mainly for information search and communication. Respondents perceived that overall work efficiency and productivity significantly increased with computer use. The complexity of software is the major barrier encountered so training is the most needed support by the department. Strategic promotion on the use of specialized software should be targeted to the management team of the hospitals/facilities.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1191-1192
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• 2015

기존의 유사 시퀀스 검색 방법들은 시퀀스 간의 거리를 이용하여 유사도를 판단하였다. 그러나 이러한 방법은 시퀀스의 형태를 고려하지 못하는 문제가 있다. 본 논문에서는 시퀀스를 쉬프팅하여 형태를 고려하고 시퀀스 간의 거리를 이용해 유사한 시퀀스를 검색하는 방법을 제안하고자 한다.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.495-502
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• 2013

Motion estimation (ME) that limits the performance of image quality and encoding speed has been developed to reduce temporal redundancy in video sequences and plays an important role in digital video compression. But it is computational demanding part of the encoder. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. ME for Multi-view video requires high computational complexity. To reduce computational complexity and maintain the image quality, a fast motion estimation method is proposed in this paper. The proposed method uses a hierarchical search strategy. This strategy method consists of modified diamond search patten, multi gird diamond search pattern, and raster search pattern. These search patterns place search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum or exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over TZ search method (JMVC) can be up to 1.2 ~3 times faster while maintaining similar video quality and bit rates.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.203-213
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• 2014

In this study, we proposed a new model with ISOIA (Insect Search by Observation based on Insect Appearance) method based on observation by insect appearance to improve user satisfaction, and compared it with the ISBC and ISOBC methods. In order to test these three insect search systems with AHP method, we derived three evaluation criteria for user satisfaction and three sub-evaluation criteria by evaluation criterion. In the ecological environment, non-experts need insect search systems to identify insect species and to get u-Learning contents related to the insects. To assist the public the non-experts, ISBC (Insect Search by Biological Classification) method based on biological classification to search insects and ISOBC (Insect Search by Observation based on Biological Classification) method based on the inference that identifies the observed insect through observation according to biological classification have been provided. In the test results, we found the order of priorities was ISOIA, ISOBC, and ISBC. It shows that the ISOIA system proposed in this study is superior in usage and quality compared with the previous insect search systems.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.451-464
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• 2016

Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.77-90
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• 2018

Software Defect Prediction (SDP) is a field of study that identifies defective modules. With insufficient local data, a company can exploit Cross-Project Defect Prediction (CPDP), a way to build a classifier using dataset collected from other companies. Most machine learning algorithms for SDP have used more than one parameter that significantly affects prediction performance depending on different values. The objective of this study is to propose a parameter selection technique to enhance the performance of CPDP. Using a Harmony Search algorithm (HS), our approach tunes parameters of cost-sensitive boosting, a method to tackle class imbalance causing the difficulty of prediction. According to distributional characteristics, parameter ranges and constraint rules between parameters are defined and applied to HS. The proposed approach is compared with three CPDP methods and a Within-Project Defect Prediction (WPDP) method over fifteen target projects. The experimental results indicate that the proposed model outperforms the other CPDP methods in the context of class imbalance. Unlike the previous researches showing high probability of false alarm or low probability of detection, our approach provides acceptable high PD and low PF while providing high overall performance. It also provides similar performance compared with WPDP.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.639-641
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• 2018

고전적으로 이용되던 디렉터리 분류로는 원하는 정보를 빠르게 찾기 어려워지면서, 키워드 기반 검색 시스템이 정보 처리의 중심이 되고 있다. 본 논문에서는 개인용 컴퓨터에서의 빠른 자료 검색을 위한 키워드 기반 정보검색 시스템을 제안한다. 시스템에서는 동적 색인을 통하여 기존 시스템들보다 빠른 시간 내에 검색 결과를 제공한다. 내용 기반 검색과 다양한 포맷에 대한 문서 검색 기능을 포함하여 사용자에게 편리한 환경을 제공할 뿐만 아니라, 한글 문장이 포함된 문서에 대해서 원활한 검색을 제공하고자 한다. 성능 비교 검증을 수행한 결과 기존 시스템에 비해 보다 빠른 시간 내에 많은 문서를 탐지할 수 있음을 확인하였다.