• 제목/요약/키워드: Segment similarity

검색결과 80건 처리시간 0.029초

Trajectory Distance Algorithm Based on Segment Transformation Distance

  • Wang, Longbao;Lv, Xin;An, Jicun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권4호
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    • pp.1095-1109
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    • 2022
  • Along with the popularity of GPS system and smart cell phone, trajectories of pedestrians or vehicles are recorded at any time. The great amount of works had been carried out in order to discover traffic paradigms or other regular patterns buried in the huge trajectory dataset. The core of the mining algorithm is how to evaluate the similarity, that is, the "distance", between trajectories appropriately, then the mining results will be accordance to the reality. Euclidean distance is commonly used in the lots of existed algorithms to measure the similarity, however, the trend of trajectories is usually ignored during the measurement. In this paper, a novel segment transform distance (STD) algorithm is proposed, in which a rule system of line segment transformation is established. The similarity of two-line segments is quantified by the cost of line segment transformation. Further, an improvement of STD, named ST-DTW, is advanced with the use of the traditional method dynamic time warping algorithm (DTW), accelerating the speed of calculating STD. The experimental results show that the error rate of ST-DTW algorithm is 53.97%, which is lower than that of the LCSS algorithm. Besides, all the weights of factors could be adjusted dynamically, making the algorithm suitable for various kinds of applications.

Automatic Music Summarization Using Vector Quantization and Segment Similarity

  • Kim, Sang-Ho;Kim, Sung-Tak;Kim, Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • 제27권2E호
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    • pp.51-56
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    • 2008
  • In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.

무선 모바일 프록시 시스템에서 유사도 기반의 캐싱 손실 최소화 (Similarity-based Caching Replacement Loss Minimization in Wireless Mobile Proxy Systems)

  • 이종득
    • 한국항행학회논문지
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    • 제16권3호
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    • pp.455-462
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    • 2012
  • 무선 모바일 프록시 캐싱 구조에서 캐싱 교체로 인한 손실은 스트리밍 QoS에 중요한 영향을 미친다. 본 논문에서는 캐싱 교체 과정에서 발생하는 손실을 최소화하기 위하여 유사도 기반의 캐싱 손실 최소화 기법 SCLM(Similarity-based Caching Loss Minimization)을 제안한다. 제안된 기법은 객체 세그먼트를 분할 한 후 유사도 관계를 수행한다. 유사도 관계가 수행된 세그먼트들은 SRT (Similarity Relation Tree)가 생성되고 유사도가 측정된다. 유사도는 적합성 피드백을 결정하는 중요한 척도로서 적합성을 만족한 세그먼트들은 캐싱 교체를 위해 캐시 블록에 저장한다. 시뮬레이션 결과 제안된 기법은 prefix 캐싱 기법, segment 캐싱 기법, 그리고 bps 캐싱 기법에 비해서 캐싱 시작 지연 제어율, 캐시 처리율, 그리고 캐시 응답율의 QoS가 효율적임을 보인다.

워핑 변환을 이용한 심전도 신호의 ST 분절 특징 값 강화 (Enhancement of ST-segment Features in ECG Signals by Warping Transformation)

  • 신승원;김경섭
    • 전기학회논문지
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    • 제59권6호
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    • pp.1143-1149
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    • 2010
  • In this study, we propose a novel method to detect and enhance the feature of ST-segment which offers the crucial information for the diagnosis of myocardial infarction and ischemia. With this aim, PQRST features of Electrocardiogram initially are detected and subsequently ST-segment are estimated. And Dynamic Time Warping(DTW) transformation is applied recursively to minimize the difference in time between ST-segments and calculate the minimum cumulative distance that decides the degree of similarity among ST-segments. As of the results, the inherent characteristic of ST-segment can be emphasized in terms of time parameter and thus the diagnostic features of a ST-segment can be revealed further.

Research on Keyword-Overlap Similarity Algorithm Optimization in Short English Text Based on Lexical Chunk Theory

  • Na Li;Cheng Li;Honglie Zhang
    • Journal of Information Processing Systems
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    • 제19권5호
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    • pp.631-640
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    • 2023
  • Short-text similarity calculation is one of the hot issues in natural language processing research. The conventional keyword-overlap similarity algorithms merely consider the lexical item information and neglect the effect of the word order. And some of its optimized algorithms combine the word order, but the weights are hard to be determined. In the paper, viewing the keyword-overlap similarity algorithm, the short English text similarity algorithm based on lexical chunk theory (LC-SETSA) is proposed, which introduces the lexical chunk theory existing in cognitive psychology category into the short English text similarity calculation for the first time. The lexical chunks are applied to segment short English texts, and the segmentation results demonstrate the semantic connotation and the fixed word order of the lexical chunks, and then the overlap similarity of the lexical chunks is calculated accordingly. Finally, the comparative experiments are carried out, and the experimental results prove that the proposed algorithm of the paper is feasible, stable, and effective to a large extent.

Perceptional Change of a New Product, DMB Phone

  • Kim, Ju-Young;Ko, Deok-Im
    • 마케팅과학연구
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    • 제18권3호
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    • pp.59-88
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    • 2008
  • Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

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무선 모바일 스트리밍 미디어 서비스를 위한 객체 세그먼트 그룹화 (Object Segment Grouping for Wireless Mobile Streaming Media Services)

  • 이종득
    • 디지털융복합연구
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    • 제10권4호
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    • pp.199-206
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    • 2012
  • 최근에 무선 모바일 네트워크상에서 모바일 클라이언트 요청증가로 인하여 스트리밍 미디어 객체를 관리하고 서비스하기 위한 새로운 기법이 제안되고 있다. 본 논문에서는 무선 모바일 네트워크상에서 스트리밍 미디어 서비스의 성능을 향상시키기 위한 새로운 객체 세그먼트 그룹화 방법을 제안한다. 제안된 기법은 분할된 객체 세그먼트들에 대해서 유사성 척도를 수행하며, 유사성 척도를 위해 disjunction, conjunction, 그리고 filtering연산을 수행한다. 이들 연산 척도에 따라 분할된 세그먼트들의 그룹화가 결정되며, 스트리밍 미디어 서비스 성능이 결정된다. 시뮬레이션 결과 제안된 기법은 처리율, 평균 시작지연, 그리고 캐시 히트율의 성능이 우수함을 보였다.

영역분할을 사용한 동영상 데이터 장면 분할 기법 (Video Data Scene Segmentation Method Using Region Segmentation)

  • 염성주;김우생
    • 정보처리학회논문지B
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    • 제8B권5호
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    • pp.493-500
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    • 2001
  • 동영상 데이터의 장면 분할은 내용기반 분석을 위해 필요한 기초작업이다. 본 논문에서는 동영상의 매 프레임을 워터쉐드 알고리즘을 통해 객체 중심의 작은 영역들로 나누어 각 영역이 연속적인 프레임 상에서 계속 존재하는가를 파악하는 방법을 통해 장면을 구분하는 새로운 영역기반 장면 분할 기법을 제안한다. 이를 위해 각 영역들에 대한 형태와 공간상의 유사도를 측정해 영역들의 움직임 정도에 따라 동영상 데이터를 동적 구간과 정적 구간으로 나누고 인접한 구간간의 유사도에 따라 그룹화 하는 방법을 통해 장면 분할을 시도한다. 제안하는 기법은 객체들을 표현하는 각 영역을 비교 대상으로 삼기 때문에 명암 변화나 변화에도 오검출 하지 않으면서 효과적으로 장면을 구분해낼수 있는 장점을 갖는다.

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Clustering 기법과 Fuzzy 기법을 이용한 영상 분할과 라벨링 (Image Segmentation and Labeling Using Clustering and Fuzzy Algorithm)

  • 이성규;김동기;강이석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.241-241
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    • 2000
  • In this Paper, we present a new efficient algorithm that can segment an object in the image. There are many algorithms for segmentation and many studies for criteria or threshold value. But, if the environment or brightness is changed, their would not be suitable. Accordingly, we apply a clustering algorithm for adopting and compensating environmental factors. And applying labeling method, we try arranging segment by the similarity that calculated with the fuzzy algorithm. we also present simulations for searching an object and show that the algorithm is somewhat more efficient than the other algorithm.

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다중레벨 벡터양자화 기반의 유사도를 이용한 자동 음악요약 (Automatic Music Summarization Using Similarity Measure Based on Multi-Level Vector Quantization)

  • 김성탁;김상호;김회린
    • The Journal of the Acoustical Society of Korea
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    • 제26권2E호
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    • pp.39-43
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    • 2007
  • Music summarization refers to a technique which automatically extracts the most important and representative segments in music content. In this paper, we propose and evaluate a technique which provides the repeated part in music content as music summary. For extracting a repeated segment in music content, the proposed algorithm uses the weighted sum of similarity measures based on multi-level vector quantization for fixed-length summary or optimal-length summary. For similarity measures, count-based similarity measure and distance-based similarity measure are proposed. The number of the same codeword and the Mahalanobis distance of features which have same codeword at the same position in segments are used for count-based and distance-based similarity measure, respectively. Fixed-length music summary is evaluated by measuring the overlapping ratio between hand-made repeated parts and automatically generated ones. Optimal-length music summary is evaluated by calculating how much automatically generated music summary includes repeated parts of the music content. From experiments we observed that optimal-length summary could capture the repeated parts in music content more effectively in terms of summary length than fixed-length summary.