• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.363-372
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• 2019

A sequence refers to data in which the order exists on the two items, and purchase transaction data in which the products purchased by one customer are listed is one of the representative sequence data. In general, all goods have a product taxonomy, such as category/ sub-category/ sub-sub category, and if they are similar to each other, they are classified into the same category according to their characteristics. Therefore, in this paper, we not only consider the purchase order of products to compare two purchase transaction sequences, but also calculate their similarity by giving a higher score if they are in the same category in spite of their difference. Especially, in order to choose the best similarity measure that directly affects the calculation performance of the purchase transaction sequences, we have compared the performance of three representative similarity measures, the Levenshtein distance, dynamic time warping distance, and the Needleman-Wunsch similarity. We have extended the existing methods to take into account the product taxonomy. For conventional similarity measures, the comparison of goods in two sequences is calculated by simply assigning a value of 0 or 1 according to whether or not the product is matched. However, the proposed method is subdivided to have a value between 0 and 1 using the product taxonomy tree to give a different degree of relevance between the two products, even if they are different products. Through experiments, we have confirmed that the proposed method was measured the similarity more accurately than the previous method. Furthermore, we have confirmed that dynamic time warping distance was the most suitable measure because it considered the degree of association of the product in the sequence and showed good performance for two sequences with different lengths.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.337-346
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• 2006

In order to analyze the behavior of moving objects, a measure for determining the similarity of trajectories needs to be defined. Although research has been conducted that retrieved similar trajectories of moving objects in Euclidean space, very little research has been conducted on moving objects in the space defined by road networks. In terms of real applications, most moving objects are located in road network space rather than in Euclidean space. In similarity measure between trajectories, however, previous methods were based on Euclidean distance and only considered spatial similarity. In this paper, we define similarity measure based on POI and TOI in road network space. With this definition, we present methods to retrieve similar trajectories using spatio-temporal similarity between trajectories. We show clustering results for similar trajectories. Experimental results show that similar trajectories searched by each method and consistency rate between each method for the searched trajectories.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.23-23
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• 2022

하천의 유량 및 유사량 자료는 하천에서 발생하는 다양한 문제를 분석하기 위한 기초자료로 지속적인 모니터링을 통한 측정자료의 생산이 필요하다. 따라서, 국내에서는 지속적인 유량 측정을 목적으로 전국의 주요 국가하천을 대상으로 약 62개소에서 H-ADCP를 활용하여 지속적인 유량측정을 수행하고 있다. 이때, H-ADCP는 유량을 측정하기 위한 유속자료와 함께 초음파산란도 자료를 부가적으로 제공하고 있어 초음파산란도를 부유사농도의 지표로 활용하여 지속적인 부유사농도를 측정하기 위한 연구가 수행되고 있으며, 기존에 설치된 자동유량관측소의 H-ADCP를 통해서 실시간의 유량자료와 함께 유사량 자료를 제공할 수 있을 것으로 기대되고 있다. 이에 본 연구에서는 자동유량관측소를 대상으로 과거 유사량 측정을 수행한 5개 지점을 선정하여 초음파산란도를 활용한 부유사농도 측정 기술의 적용성을 검토하였고, 이를 통해 제시한 부유사농도 측정 방법을 통해 실시간 부유사농도 측정 시스템을 개발하였다. 그리고 실시간 부유사농도 측정 시스템의 적용성을 검토하기 위해 나주시(남평교) 자동유량관측소 지점에 시스템을 구축하여 초음파기반의 부유사농도 측정 기술을 통한 실시간 부유사농도 산정 방법에 대한 보완 사항과 개선방향을 도출하고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1404-1407
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• 2007

본 논문에서는 객관식 문항을 난이도에 따라 자동으로 생성하는 방법을 고안하여, 학습자 수준에 적합하도록 다양하고 동적인 형태로 문항 제시를 할 수 있는 시스템을 제안하였다. 이를 위해서는 주어진 문장에서 형태소 분석을 통해 키워드를 추출하고, 각 키워드에 대하여 워드넷의 계층적 특성에 따라 의미가 유사한 후보 단어를 제시한다. 의미 유사 후보 단어를 제시할 때, 워드넷에서의 어휘간 유사도 측정 방법을 사용함으로써 생성된 문항의 난이도를 사용자가 원하는 수준으로 조정할 수 있도록 하였다. 단어의 의미 유사도는 동의어를 의미하는 수준 0에서 거의 유사도를 찾을 수 없는 수준 9 까지 다양하게 제시할 수 있으며, 이를 조절함으로써 문항의 전체 난이도를 조절할 수 있다. 후보 어휘들의 의미 유사도 측정을 위해서, 본 논문에서는 두 가지 방법을 사용하여 구현하였다. 첫째는 단순히 두 어휘의 워드넷 상에서의 거리만을 고려한 것이고 둘째는 두 어휘가 워드넷에서 차지하는 비중까지 추가적으로 고려한 것이다. 이러한 방법을 통하여 실제 출제자가 기존에 출제된 문제를 토대로 보다 다양한 내용과 난이도를 가진 문제 또는 문항을 보다 쉽게 출제하게 함으로써 출제에 소요되는 비용을 줄일 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.402-405
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• 2012

문서와 문서간의 유사도들 측정하는 방법 은 크게 지문법 (fingerprint)을 이용한 방법과 서열 정렬(sequence alignment)알고리즘을 이용한 방법이 있다. 두 방법은 각각 속도와 정확도라는 장점을 가지고 있다. 다단계정렬(MLA, Multi-Level alignment))는 이러한 두 방법을 조합하여 탐색 속도와 정확도 사이의 비중을 사용자가 결정할 수 있도록 하기 위한 방법이다.[1] 다단계 정렬은 두 문서를 단위 블록(basis block)로 나누고 블록 간의 벡터를 비교하여 유사도를 측정하게 되는데, 본 연구에서는 초성 추출 및 어간 추출을 통해 단위 블록의 벡터를 빠른 시 간에 생성하고 비교하는 방법과 다단계 탐색을 통해 정확도를 유지하면서 빠르게 유사도를 측정하는 방식에 대해 설명한다. 실험결과 제안 방법을 통해 다단계 정렬 방법을 이용한 대용량 문서 비교의 속도가 2 배 이상 빨라짐을 보인다.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.179-193
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• 2003

Clustering is a data mining method which help discovering interesting data groups in large databases. In traditional data clustering, similarity between objects in the cluster is measured by pairwise similarity of objects. But we devise an advanced measurement called item similarity in this paper, in terms of nature of clustering transaction data and use this measurement to perform clustering. This new algorithm show the similarity by accepting the concept of relationship between different attributes. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.104-112
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• 2010

Social bookmarking is one of the most interesting trends in the current web environment. In a social bookmarking system, users annotate a web page with tags, which describe the contents of the page. Numerous studies have been done using this information, mostly on enhancing the quality of web search. In this paper, we use this information to measure the semantic similarity between two web pages. Since web pages consist of various types of multimedia data, it is quite difficult to compare the semantics of two web pages by comparing the actual data contained in the pages. With the help of social bookmarks, this comparison can be performed very effectively. In this paper, we propose a new similarity measure between web pages, called Web Page Similarity Based on Entire Tags (WSET), based on social bookmarks. The experimental results show that the proposed measure yields more satisfactory results than the previous ones.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.61-69
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• 2009

This paper presents an improved method measuring inter-utterance similarity in an example-based dialogue system, which searches the most similar utterance in a dialogue database to generate a response to a given user utterance. Unlike general inter-sentence similarity measures, the inter-utterance similarity measure for example-based dialogue system should consider not only word distribution but also various linguistic features, such as affirmation/negation, tense, modality, sentence type, which affects the natural conversation. However, previous approaches do not sufficiently reflect these features. This paper proposes a new utterance similarity measure by analyzing and reflecting various linguistic features to improve performance in accuracy. Also, by considering substitutability of the features, the proposed method can utilize limited number of examples. Experimental results show that the proposed method achieves 10%p improvement in accuracy compared to the previous method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.39-47
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• 2023

In this paper, we propose a method to measure the similarity between golf swings in videos. As it is known that deep learning-based artificial intelligence technology is effective in the field of computer vision, attempts to utilize artificial intelligence in video-based sports data analysis are increasing. In this study, the joint coordinates of a person in a golf swing video were obtained using a deep learning-based pose estimation model, and based on this, the similarity of each swing segment was measured. For the evaluation of the proposed method, driver swing videos from the GolfDB dataset were used. As a result of measuring swing similarity by pairing swing videos of a total of 36 players, 26 players evaluated that their other swing sequence was the most similar, and the average ranking of similarity was confirmed to be about 5th. This ensured that the similarity could be measured in detail even when the motion was performed similarly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.585-588
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• 2008

This paper proposes hand gesture recognition using shape similarity method. For this, we require two steps which are aquisition of Hand area and similarity evaluation. First step is extracting hand area using YCbCr color spare. Then eliminate noise through filter and analyzing histogram. For doing this, we ran measure similarity of hand gesture by applying TSR after getting contour. Finally, we utilize shape similarity for recognizing of hand gesture.