• International Journal of Contents
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• 제17권4호
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• pp.1-15
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• 2021

Named entity recognition (NER) is a crucial task for NLP, which aims to extract information from texts. To build NER systems, deep learning (DL) models are learned with dictionary features by mapping each word in the dataset to dictionary features and generating a unique index. However, this technique might generate noisy labels, which pose significant challenges for the NER task. In this paper, we proposed DL-dictionary features, and evaluated them on two datasets, including the OntoNotes 5.0 dataset and our new infectious disease outbreak dataset named GFID. We used (1) a Bidirectional Long Short-Term Memory (BiLSTM) character and (2) pre-trained embedding to concatenate with (3) our proposed features, named the Convolutional Neural Network (CNN), BiLSTM, and self-attention dictionaries, respectively. The combined features (1-3) were fed through BiLSTM - Conditional Random Field (CRF) to predict named entity classes as outputs. We compared these outputs with other predictions of the BiLSTM character, pre-trained embedding, and dictionary features from previous research, which used the exact matching and partial matching dictionary technique. The findings showed that the model employing our dictionary features outperformed other models that used existing dictionary features. We also computed the F1 score with the GFID dataset to apply this technique to extract medical or healthcare information.

• Asia pacific journal of information systems
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• 제18권1호
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• pp.79-96
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• 2008

One of the roles of the Semantic Web services is to execute dynamic intra-organizational services including the integration and interoperation of business processes. Since different organizations design their processes differently, the retrieval of similar semantic business processes is necessary in order to support inter-organizational collaborations. Most approaches for finding services that have certain features and support certain business processes have relied on some type of logical reasoning and exact matching. This paper presents our approach of using imprecise matching for expanding results from an exact matching engine to query the OWL(Web Ontology Language) MIT Process Handbook. MIT Process Handbook is an electronic repository of best-practice business processes. The Handbook is intended to help people: (1) redesigning organizational processes, (2) inventing new processes, and (3) sharing ideas about organizational practices. In order to use the MIT Process Handbook for process retrieval experiments, we had to export it into an OWL-based format. We model the Process Handbook meta-model in OWL and export the processes in the Handbook as instances of the meta-model. Next, we need to find a sizable number of queries and their corresponding correct answers in the Process Handbook. Many previous studies devised artificial dataset composed of randomly generated numbers without real meaning and used subjective ratings for correct answers and similarity values between processes. To generate a semantic-preserving test data set, we create 20 variants for each target process that are syntactically different but semantically equivalent using mutation operators. These variants represent the correct answers of the target process. We devise diverse similarity algorithms based on values of process attributes and structures of business processes. We use simple similarity algorithms for text retrieval such as TF-IDF and Levenshtein edit distance to devise our approaches, and utilize tree edit distance measure because semantic processes are appeared to have a graph structure. Also, we design similarity algorithms considering similarity of process structure such as part process, goal, and exception. Since we can identify relationships between semantic process and its subcomponents, this information can be utilized for calculating similarities between processes. Dice's coefficient and Jaccard similarity measures are utilized to calculate portion of overlaps between processes in diverse ways. We perform retrieval experiments to compare the performance of the devised similarity algorithms. We measure the retrieval performance in terms of precision, recall and F measure? the harmonic mean of precision and recall. The tree edit distance shows the poorest performance in terms of all measures. TF-IDF and the method incorporating TF-IDF measure and Levenshtein edit distance show better performances than other devised methods. These two measures are focused on similarity between name and descriptions of process. In addition, we calculate rank correlation coefficient, Kendall's tau b, between the number of process mutations and ranking of similarity values among the mutation sets. In this experiment, similarity measures based on process structure, such as Dice's, Jaccard, and derivatives of these measures, show greater coefficient than measures based on values of process attributes. However, the Lev-TFIDF-JaccardAll measure considering process structure and attributes' values together shows reasonably better performances in these two experiments. For retrieving semantic process, we can think that it's better to consider diverse aspects of process similarity such as process structure and values of process attributes. We generate semantic process data and its dataset for retrieval experiment from MIT Process Handbook repository. We suggest imprecise query algorithms that expand retrieval results from exact matching engine such as SPARQL, and compare the retrieval performances of the similarity algorithms. For the limitations and future work, we need to perform experiments with other dataset from other domain. And, since there are many similarity values from diverse measures, we may find better ways to identify relevant processes by applying these values simultaneously.

• 정보처리학회논문지D
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• 제12D권5호
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• pp.789-796
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• 2005

현재 대부분의 도서관 정보검색 시스템들은 키워드 정합매칭(exacting matching) 방법으로 검색 서비스를 제공하고 있으므로, 검색 결과의 양이 방대하고 비적합한 결과가 많이 포함되어 있다. 따라서 본 논문에서는 키워드기반 검색 엔진의 단점을 보완하고 현재 도서관 검색 환경을 고려하여 보다 적합한 결과를 사용자에게 신속하게 제공하기 위하여 전공분류표와 사용자 프로파일을 이용한 검색 모델 SULRM(Retrieval Model using Subject Classification Table, User Profile & LSI)을 제안한다. SULRM은 키워드 검색 결과로 얻은 자료들을 분류된 자료의 경우와 미분류된 자료의 경우로 나누어, 분류된 자료의 경우에는 전공분류표를 생성하여 자료 필터링을 수행하고, 미분류된 자료의 경우에는 사용자 프로파일과 LSI(Latent Semantic Indexing)을 이용하여 자료의 순위를 결정해서 사용자에게 제시한다. 실험평가는 우리 대학의 디지털 도서관을 실험환경으로 하여 필터링 방법, 사용자 프로파일 갱신 방법, 그리고 문서순위결정 방법의 성능을 측정한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.323-325
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• 1993

In this paper, the decentralized suboptimal $H_2$ filtering problem is considered. An additional term is added to the centralized optimal $H_2$ filter so that the whole filter is decentralized. We derive a sufficient condition for existence of such decentralized filters. By employing the solution procedure for the exact model matching problem, we obtain a set of decentralized $H_2$ filters, and choose a suboptimal filter from this set of decentralized $H_2$ filters. Naturally the resulting filter is guaranteed to be stable.

• 한국측량학회지
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• 제32권6호
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• pp.625-635
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• 2014

Multiple strips are required for large area mapping using ALS (Airborne Laser Scanner) system. LiDAR (Light Detection And Ranging) data collected from the ALS system has discrepancies between strips due to systematic errors of on-board laser scanner and GPS/INS, inaccurate processing of the system calibration as well as boresight misalignments. Such discrepancies deteriorate the overall geometric quality of the end products such as DEM (Digital Elevation Model), building models, and digital maps. Therefore, strip adjustment for minimizing discrepancies between overlapping strips is one of the most essential tasks to create seamless point cloud data. This study implemented area-based matching (ABM) to determine conjugate features for computing 3D transformation parameters. ABM is a well-known method and easily implemented for this purpose. It is obvious that the exact same LiDAR points do not exist in the overlapping strips. Therefore, the term "conjugate point" means that the location of occurring maximum similarity within the overlapping strips. Coordinates of the conjugate locations were determined with sub-pixel accuracy. The major drawbacks of the ABM are sensitive to scale change and rotation. However, there is almost no scale change and the rotation angles are quite small between adjacent strips to apply AMB. Experimental results from this study using both simulated and real datasets demonstrate validity of the proposed scheme.

• 한국전산구조공학회논문집
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• 제31권2호
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• pp.71-78
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• 2018

본 연구에서는 NURBS 기반 아이소 지오메트릭 쉘 해석을 위해 다중 패치 해석 모델을 정식화하였다. 기존 연구를 통해 개발된 단일 패치로 구성된 전단 변형을 고려한 쉘 요소에 대해 일반 좌표계에서 기하학적으로 엄밀한 쉘 구조물의 아이소 지오메트릭 해석 모델을 도입하고 매개변수 연속성을 고려하여 다중 패치 모델로 확장하였다. 인접 곡면의 노트 요소가 결합 경계를 통해 조화를 이루는 경우에 대해 0차와 1차 매개변수 연속성 조건을 고려하였으며, 두 패치 간 마스터-슬레이브 관계를 정립하여 종속된 한 곡면의 자유도를 상대 곡면의 자유도로 표시하여 모델 크기를 줄이면서 두 곡면을 결합하였다. 다중 패치 쉘 예제에 대해 0차와 1차 연속성 조건을 각각 적용하여 구조해석을 수행하여 1차 연속성 조건의 주요한 특성들을 확인하였다. 또한 각 연속성 조건에 대한 해의 수렴 특성을 검토하였으며 결합 경계에서의 두 패치의 연속성을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.585-588
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• 2010

건물 내에서 특정 사용자의 현 위치를 예측하는 문제는 방문자의 안내 등 다양하게 응용될 수 있다. 이 문제를 풀기 위해 기존 방법들은 사용자가 과거에 이동한 패턴을 한정된 길이만큼만 고려하여 예측한다. 이는 복잡한 이동 패턴을 모델링 할 수 없고, 단순한 이동 패턴은 필요 이상으로 상세히 모델링함으로써 시스템의 효율을 떨어뜨림은 물론이고, 예측 오류를 야기한다. 본 논문에서는 기존의 방법들과는 달리 최근 이동 경로의 길이에 제한을 두지 않고 이동 패턴을 구분하는데 필요한 만큼만 고려하여 예측 결과를 도출하고자 한다. 이를 위해 탐색 트리를 사용하는데, 이 탐색 트리는 위치 예측에 필요한 만큼만 장소를 비교하도록 구성된다. 이 탐색 트리는 효율적이고 정확한 예측을 가능하게 해준다.

• Journal of Communications and Networks
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• 제12권4호
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• 전자공학회논문지CI
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• 제48권1호
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• pp.1-7
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• 2011

3차원 지도(3D Map)를 구축하기 위해서는 지형정보와 지도상에서 건물 영역 및 건물 형상 정보가 필요하다. 이를 위해 본 논문에서는 개선된 스네이크(Snake) 알고리즘으로 건물 영역을 반자동으로 추출하는 방법을 제안한다. 본 방법은 전처리, 제어점의 초기화, 개선된 스네이크 알고리즘 적용 세 단계로 구성한다. 첫 번째 단계에서는 위생영상을 그레이 영상으로 변환 후 근사 에지를 추출하여 그레이 영상과 합성한다. 두 번째 단계에서는 사용자가 건물의 중심점을 설정한 후 원형 또는 사각형 모양의 초기 제어점을 계산하여 설정한다. 세번째 단계에서는 개선된 스네이크 알고리즘을 적용하여 건물영역을 추출한다. 이러한 과정에서 스네이크 에너지 계산식의 한 항을 새로운 방법으로 설정하여 건물영역 추출용으로 특화하였다. 그리고 스카이 뷰의 위성영상을 이용하여 제안된 방법을 건물영역 매칭율을 평가하였는데 75%의 매칭율을 보였다.

• 패션비즈니스
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• 제21권6호
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• pp.47-65
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• 2017

This study is intended to compare an actual wedding dress being made completely through 3D software, and compare it with an actual dress of a real model by using collective tools for comparative analysis. The method of the study was conducted via a literature review along with the production of the dresses. In the production, two wedding dresses for the small wedding ceremony were designed. Each of the design was made into both 3D and an actual garment. The results are as follows. First, the 3D whole body scanner reflects the measure of the exact human body size, however there were some difficulties in matching what the customer wanted, because the difference of the skin color and the hair style. Second, the pattern of the dress is much more easily altered than it was in the real production. Third, the silhouette of the virtual and the actual person with the dress was nearly the same. Fourth, textile tool was much more convenient because of the use of real-time rendering on the virtual dresses. Lastly, the lace and biz decoration were flat, and the luster was duller than in reality. Prospectively, the consumer will decide their own design of variety through the use of the avatar without wearing the actual dresses, and they would demand what the another one desired, different from the presented ones by making the corrections by themselves. Through this process, the consumer would be actively participating in the design, a step which would finally lead to the two way designing rather than the one way design of present times.