Characteristics of the similarity index in a Korean medical journal

정승현,이윤석,이정혁,박하연,김대환 대한마취통증의학회 2017 Korean Journal of Anesthesiology Vol.70 No.3

Background: Journal editors have exercised their control over submitted papers having a high similarity index. Despite widespread suspicion of possible plagiarism on a high similarity index, our study focused on the real effect of the similarity index on the value of a scientific paper. Methods: This research examined the percent values of the similarity index from 978 submitted (420 published) papers in the Korean Journal of Anesthesiology since 2012. Thus, this study aimed to identify the correlation between the similarity index and the value of a paper. The value of a paper was evaluated in two distinct phases (during a peer-review process vs. after publication), and the value of a published paper was evaluated in two aspects (academic citation vs. social media appearance). Results: Yearly mean values of the similarity index ranged from 16% to 19%. There were 254 papers cited at least once and 179 papers appearing at least once in social media. The similarity index affected the acceptance/rejection of a paper in various ways; although the influence was not linear and the cutoff measures were distinctive among the types of papers, both extremes were related to a high rate of rejection. After publication, the similarity index had no effect on academic citation or social media appearance according to the paper. Conclusions: The finding suggested that the similarity index no longer had an influence on academic citation or social media appearance according to the paper after publication, while the similarity index affected the acceptance/rejection of a submitted paper. Proofreading and intervention for finalizing the draft by the editors might play a role in achieving uniform quality of the publication.

왜곡 제거 시계열 서브시퀀스 매칭에서 빠른 인덱스 구성법

길명선(Myeong-Seon Gil),김범수(Bum-Soo Kim),문양세(Yang-Sae Moon),김진호(Jinho Kim) 한국정보과학회 2011 정보과학회논문지 : 데이타베이스 Vol.38 No.6

본 논문에서는 왜곡 제거 시계열 서브시퀀스 매칭에서 인덱스를 효율적으로 구성하는 방법을 다룬다. 기존의 왜곡 제거 시계열 서브시퀀스 매칭에서는 인덱스 구축에 매우 많은 시간이 걸리는데, 이는 왜곡 제거의 모든 가능한 경우를 고려하기 위해 너무 많은 윈도우가 생성되기 때문이다. 실제로 길이 30 만의 시계열인 경우에도 인덱스 구축을 위해 약 100분의 많은 시간이 걸려, 대용량 시계열 데이터에 대해서는 인덱스 구축이 매우 어려운 단점이 있다. 본 논문에서는 기존 인덱스 구축 과정을 단계별로 정형적으로 분석한 후, 각 단계별 성능 극대화 방법을 제안한다. 특히, 동적 프로그래밍 기법을 이용하여 PAA- 버킷 및 DF-버킷(distortion-free bucket)의 개념을 제안하는데, 이는 반복되는 계산 결과를 저장-후-재 사용(store-and-reuse)하는 기법으로, 이를 사용하여 기존 방법에 비해 효율적인 인덱스 구축이 가능하다. 본 논문에서는 복잡도 분석 및 실험 평가를 통해 제안한 방법의 우수성을 입증한다. In this paper we present an efficient approach of constructing a multidimensional index in distortion-free time-series subsequence matching. Index construction of previous distortion-free subsequence matching algorithms is a very time-consuming process since it generates a huge number of windows to consider all possible positions and all possible query lengths. According to the real experiment, the index construction time reaches approximately 100 minutes for a time-series of length 300K, and this means that the index construction itself is very difficult for very large time-series databases. To solve this problem, in this paper we first thoroughly analyze the index construction steps, then discuss how to improve the performance of each step, and finally propose two advanced algorithms of efficiently constructing an index. In particular, by exploiting dynamic programming techniques, we present the concepts of PAA-bucket and DF(distortion-free)-bucket, which store-and-reuse the intermediate results repeatedly computed. Through the store-and-reuse technique, the proposed algorithms construct a multidimensional index very faster than the previous algorithm. Through analytical and empirical evaluations, we showcased the superiority of the proposed algorithms.

Efficient Document Similarity Detection Using Weighted Phrase Indexing

Papias Niyigena,Zhang Zuping,Mansoor Ahmed Khuhro,Damien Hanyurwimfura 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5

Document similarity techniques mostly rely on single term analysis of the document in the data set. To improve the efficiency and effectiveness of the process of document similarity detection, more informative feature terms have been developed and presented by many researchers. In this paper, we present phrase weight index, which indexes documents in the data set based on important phrases. Phrasal indexing aims to reduce the ambiguity inherent to the words considered in isolation, and then improve the effectiveness in document similarity computation. The method we are presenting here in this paper inherit the term tf-idf weighting scheme in computing important phrases in the collection. It computes the weight of phrases in the document collection and according to a given threshold; the important phrases are identified and are indexed. The data dimensionality which hinders the performance of document similarity for different methods is solved by an offline index creation of important phrases for every document. The evaluation experiments indicate that the presented method is very effective on document similarity detection and its quality surpasses the traditional phrase-based approach in which the reduction of dimensionality is ignored and other methods which use single-word tf-idf.

FM-index of alignment: A compressed index for similar strings

Na, J.C.,Kim, H.,Park, H.,Lecroq, T.,Leonard, M.,Mouchard, L.,Park, K. North-Holland Pub. Co ; Elsevier Science Ltd 2016 Theoretical computer science Vol.638 No.-

<P>In this paper we propose the FM-index of alignment, a compressed index for similar strings with the functionalities of pattern search and random access. For this, we first design a new and improved version of the suffix array of alignment. The FM-index of alignment is an FM-index of this suffix array of alignment. The FM-index of alignment supports the LF-mapping and backward search, the key functionalities of the FM-index, but the LF-mapping and backward search of our index is significantly more involved than the original FM index. We implemented the FM-index of alignment and did experiments on 100 genome sequences from the 1000 Genomes Project. The index size of the FM-index of alignment is about a half of that of RLCSA due to Makinen et al. (C) 2015 Elsevier B.V. All rights reserved.</P>

한국과 중국의 서비스무역 국제경쟁력에 관한 연구

안순기(Soon-Ki Ahn),송진구(Jin-Goo Song) 한국무역연구원 2021 무역연구 Vol.17 No.6

Purpose This study compares and analyzes the trends in service trade between Korea and China by analyzing the RCA index, SRCA index, and TSI index. Design/Methodology/Approach For this analysis using the UN Comtrade DB, the service trade in 11 sectors was analyzed using Extended Balance of Payments Services (EBOPS) 2002 between Korea and China for 8 years (2010 to 2018). The comparative advantage was measured by calculating the present comparative advantage index (RCA), the revealed symmetric comparative advantage (SRCA), and the trade specialization index (TSI). Then, the level of competition was measured by analyzing the export competition (ESI) of the service sectors between Korea and China. Findings In Korea and China, the transportation and construction sectors, which are highly related to manufacturing, have relatively high international competitiveness; however, international competitiveness is weakening in other service trade sectors. Research Implications In the case of royalties and license fees, if international competitiveness is weakened, as product exports increase, the size of the service deficit in that sector will inevitably increase. Accordingly, it should be human investment related to infrastructure construction and human education, such as royalties and license fees.

유사도 검색을 위한 데이터 재배열을 이용한 공간 효율적인 역 색인 기법

임마누(Manu Im),김종익(Jongik Kim) Korean Institute of Information Scientists and Eng 2015 정보과학회논문지 Vol.42 No.10

An inverted index structure is widely used for efficient string similarity search. One of the main requirements of similarity search is a fast response time; to this end, most techniques use an in-memory index structure. Since the size of an inverted index structure usually very large, however, it is not practical to assume that an index structure will fit into the main memory. To alleviate this problem, we propose a novel technique that reduces the size of an inverted index. In order to reduce the size of an index, the proposed technique rearranges data strings so that the data strings containing the same q-grams can be placed close to one other. Then, the technique encodes those multiple strings into a range. Through an experimental study using real data sets, we show that our technique significantly reduces the size of an inverted index without sacrificing query processing time.

협력필터링에서 자카드 계수에 기반한 서로 다른 유사도 척도의 적용

이수정 한국컴퓨터정보학회 2021 韓國컴퓨터情報學會論文誌 Vol.26 No.5

Sparse ratings data hinder reliable similarity computation between users, which degrades the performance of memory-based collaborative filtering techniques for recommender systems. Many works in the literature have been developed for solving this data sparsity problem, where the most simple and representative ones are the methods of utilizing Jaccard index. This index reflects the number of commonly rated items between two users and is mostly integrated into traditional similarity measures to compute similarity more accurately between the users. However, such integration is very straightforward with no consideration of the degree of data sparsity. This study suggests a novel idea of applying different similarity measures depending on the numeric value of Jaccard index between two users. Performance experiments are conducted to obtain optimal values of the parameters used by the proposed method and evaluate it in comparison with other relevant methods. As a result, the proposed demonstrates the best and comparable performance in prediction and recommendation accuracies. 희소한 평가 데이터는 사용자들 간의 신뢰할만한 유사도 산출을 저해하기 때문에 추천 시스템을위한 메모리 기반의 협력 필터링 기법의 성능을 저하시킨다. 기존 연구의 많은 결과물은 이 데이터희소성 문제를 해결하기 위해 개발되었으며, 가장 단순하고 대표적인 업적은 자카드 계수를 활용하는 방법들이다. 이 계수는 두 사용자의 공통 평가 항목수를 반영하며, 그들 간의 유사도를 보다 정확하게 계산하기 위해 전통적인 유사도 척도와 통합된다. 그러나, 그러한 통합은 데이터 희소성의 정도를 고려하지 않은 매우 단순한 방법이다. 본 연구는 두 사용자의 자카드 계수값에 의거하여 다른유사도 척도를 적용하는 새로운 아이디어를 제시한다. 제안 방법에서 사용하는 파라미터의 최적값을 구하기 위하여 성능 실험을 진행하였고, 다른 관련된 방법들과 비교 평가하였다. 결과로서, 제안방법은 예측 정확도와 추천 정확도에 있어서 가장 우수하거나 대등한 성능을 보였다.

Improving the Scalability of ALS-based Large Recommender Systems with Similar User Index

Haesung Lee,Joonhee Kwon 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.2

Alternating Least Squares (ALS) is popular method to compute matrix factorization in the parallel way. However, due to the time complexity in predicting user’s preference, ALS is not scalable to large-scale datasets. In this paper, we propose a similar user index-based parallel matrix factorization approach. Since the group of similar users is indexed in advance, there is no need to compute similarities between all users in datasets. Furthermore, the size of a matrix is reduced because the matrix is only composed of indexed user’s ratings and items. The current advanced cloud computing including Hadoop, MapReduce and Amazon EC2 are employed to implement the proposed approaches. We empirically show that the use of similar user index resolves the scalable issue of ALS and improves the performance of large scale recommender systems in distributed computing environment.

Early bolt looseness state identification via generalized variational mode decomposition and similarity index

Yanfei Guo,ZhouSuo Zhang,Wenzhan Yang,Jianbin Cao,Teng Gong 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.3

A novel method for early looseness state identification of bolted joint beams is proposed in this paper based on generalized variational mode decomposition (GVMD) and a similarity index. In the proposed method vibration signals are decomposed by GVMD, which has the property of the multiscale and fixed-frequency decomposition. To effectively extract the desired modes, the frequency band allocation is designed through flexibly defining scale parameters and prior center frequencies according to the characteristics of the signal itself and real needs. A new similarity index is formed based on the centroid frequency ratio of sensitive vibration modes to reliably identify early looseness state. The effectiveness of the proposed method is verified by impulse experiments of bolted joint transverse beam and bolted joint vertical beam. The results indicate that compared with other methods, the proposed method can effectively identify the early looseness state of the bolted joint beams, and has a good repeatability.

Numerical Objective Assessment Using Structural Similarity for Diffuse Optical Reconstructed Images

Vicky Mudeng(비키 무댕 ),Se-woon Choe(최세운) 한국정보통신학회 2021 한국정보통신학회 종합학술대회 논문집 Vol.25 No.2

본 연구의 목표는 확산 광학 단층 촬영에 대한 기준 영상을 사용하여 동질성과 이질성을 분리하기 위한 재구성된 영상들간의 수치적 평가를 위해 구조적 유사성 지수에 기초한 알고리즘을 개발한다. 글로벌 지오메트리 및 관심 영역 평가는 유사성을 산출하기 위해 측정되었으며, 그 결과 구조적 유사성 지수의 평균이 모델 내부에 가시적 포함 여부를 판단할 수 있는 잠재적 성능을 나타낸다는 것을 알 수 있으며, 구조적 유사성 지수는 유방 구조 정보를 평가하기 위한 이미지 평가를 지원 가능한 것으로 확인 되었다. The work within this study develops an algorithm based on the structural similarity index to assess numerically between reconstructed images with a reference image to separate the homogeneity and heterogeneity for diffuse optical tomography. Global geometry and region of interest assessment have been measured to yield the similarity. The results indicate that the mean of structural similarity index shows potential performance to distinguish between visible and invisible inclusion inside the model. Therefore, the structural similarity index may promise to assist the image assessment for evaluating breast structural information.