• Title/Summary/Keyword: Merging technique

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Hybrid Preference Prediction Technique Using Weighting based Data Reliability for Collaborative Filtering Recommendation System (협업 필터링 추천 시스템을 위한 데이터 신뢰도 기반 가중치를 이용한 하이브리드 선호도 예측 기법)

  • Lee, O-Joun;Baek, Yeong-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.5
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    • pp.61-69
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    • 2014
  • Collaborative filtering recommendation creates similar item subset or similar user subset based on user preference about items and predict user preference to particular item by using them. Thus, if preference matrix has low density, reliability of recommendation will be sharply decreased. To solve these problems we suggest Hybrid Preference Prediction Technique Using Weighting based Data Reliability. Preference prediction is carried out by creating similar item subset and similar user subset and predicting user preference by each subset and merging each predictive value by weighting point applying model condition. According to this technique, we can increase accuracy of user preference prediction and implement recommendation system which can provide highly reliable recommendation when density of preference matrix is low. Efficiency of this system is verified by Mean Absolute Error. Proposed technique shows average 21.7% improvement than Hao Ji's technique when preference matrix sparsity is more than 84% through experiment.

Multiple Texture Image Recognition with Unsupervised Block-based Clustering (비교사 블록-기반 군집에 의한 다중 텍스쳐 영상 인식)

  • Lee, Woo-Beom;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.9B no.3
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    • pp.327-336
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    • 2002
  • Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

Color Image Segmentation Based on Edge Salience Map and Region Merging (경계 중요도 맵 및 영역 병합에 기반한 칼라 영상 분할)

  • Kim, Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.105-113
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    • 2007
  • In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

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Logic Synthesis Algorithm for TLU-Type FPGA (TLU형 FPGA를 위한 기술 매핑 알고리즘)

  • Park, Jang-Hyeon;Kim, Bo-Gwan
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.5
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    • pp.777-786
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    • 1995
  • This paper describes several algorithms for technology mapping of logic functions into interesting and popular FPGAs that use look-up table memories. In order to improve the technology mapping for FPGA, some existing multi-level logic synthesis, decomposition reduction and packing techniques are analyzed and compared. And then new algorithms such as node-pair decomposition, merging fanin, unified reduction and multiple output decomposition which are used for combinational logic design, are proposed. The cost function is used to minimize the number of CLBs and edges of the network. The cost is a linear combination of each weight that is given by user. Finally we compare our new algorithm with previous logic design technique[8]. In an experimental comparison our algorithm requires 10% fewer CLB and nets than SIS-pga.

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The Map Generalization Methodology for Korean Cadastral Map using Topographic Map (수치지형도를 이용한 연속지적도의 지도 일반화 기법 연구)

  • Park, Woo-Jin;Lee, Jae-Eun;Yu, Ki-Yun
    • Spatial Information Research
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    • v.19 no.1
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    • pp.73-82
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    • 2011
  • Recently, demand for the use of cadastral map is increasing in both public and private area. To use cadastral map in web or mobile environment, construction of the multi-representation database(MRDB) that is the compressed into multiple scale from the original map data is recommended. In this study, the map generalization methodology for the cadastral map by applying overlay with topographic map and polygon generalization technique is suggested. This process is composed of three steps, re-constructing the network data of topographic map, polygon merging of parcel lines according to network degree, and applying line simplification techniques. Proposed methodologies are applied to the cadastral map in Suwon area. The result map was generalized into 1:5,000, 1:20,000, 1:100,000 scale, and data compression ratio was shown in 15% 8% 1% level respectively.

A Space Efficient Indexing Technique for DNA Sequences (공간 효율적인 DNA 시퀀스 인덱싱 방안)

  • Song, Hye-Ju;Park, Young-Ho;Loh, Woong-Kee
    • Journal of KIISE:Databases
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    • v.36 no.6
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    • pp.455-465
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    • 2009
  • Suffix trees are widely used in similar sequence matching for DNA. They have several problems such as time consuming, large space usages of disks and memories and data skew, since DNA sequences are very large and do not fit in the main memory. Thus, in the paper, we present a space efficient indexing method called SENoM, allowing us to build trees without merging phases for the partitioned sub trees. The proposed method is constructed in two phases. In the first phase, we partition the suffixes of the input string based on a common variable-length prefix till the number of suffixes is smaller than a threshold. In the second phase, we construct a sub tree based on the disk using the suffix sets, and then write it to the disk. The proposed method, SENoM eliminates complex merging phases. We show experimentally that proposed method is effective as bellows. SENoM reduces the disk usage less than 35% and reduces the memory usage less than 20% compared with TRELLIS algorithm. SENoM is available to query efficiently using the prefix tree even when the length of query sequence is large.

Wireless Controller with Replay Function for the Animatronics Control (애니매트로닉스 모형제어를 위한 반복재생형 무선송수신 제어기)

  • Park, Byoung-Seob;Shin, Jeong-Ho
    • The Journal of the Korea Contents Association
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    • v.8 no.10
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    • pp.45-53
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    • 2008
  • The animatronics technique could be very important fact of technique not only to achieve full completion of visible image but also to offer lots of chances to express images by merging CG, special effects and special devices. In this thesis, we design and implement the Zigbee-based wireless transceiver and communication program to control animal animatronics such as a dog and bear. The wireless control utilizing the Zigbee protocol is that electrically consumption is more small than the Bluetooth and reliability of data transmission is better. The implemented control systems and program have the normal and replay function for control of animal models. This functions and operability are tested by a designed animatronics prototype under the wireless environment.

Proposal of Image Segmentation Technique using Persistent Homology (지속적 호몰로지를 이용한 이미지 세그멘테이션 기법 제안)

  • Hahn, Hee Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.1
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    • pp.223-229
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    • 2018
  • This paper proposes a robust technique of image segmentation, which can be obtained if the topological persistence of each connected component is used as the feature vector for the graph-based image segmentation. The topological persistence of the components, which are obtained from the super-level set of the image, is computed from the morse function which is associated with the gray-level or color value of each pixel of the image. The procedure for the components to be born and be merged with the other components is presented in terms of zero-dimensional homology group. Extensive experiments are conducted with a variety of images to show the more correct image segmentation can be obtained by merging the components of small persistence into the adjacent components of large persistence.

Access efficiency of small sized files in Big Data using various Techniques on Hadoop Distributed File System platform

  • Alange, Neeta;Mathur, Anjali
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.359-364
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    • 2021
  • In recent years Hadoop usage has been increasing day by day. The need of development of the technology and its specified outcomes are eagerly waiting across globe to adopt speedy access of data. Need of computers and its dependency is increasing day by day. Big data is exponentially growing as the entire world is working in online mode. Large amount of data has been produced which is very difficult to handle and process within a short time. In present situation industries are widely using the Hadoop framework to store, process and produce at the specified time with huge amount of data that has been put on the server. Processing of this huge amount of data having small files & its storage optimization is a big problem. HDFS, Sequence files, HAR, NHAR various techniques have been already proposed. In this paper we have discussed about various existing techniques which are developed for accessing and storing small files efficiently. Out of the various techniques we have specifically tried to implement the HDFS- HAR, NHAR techniques.

Conjoint analysis by merging attributes (속성 병합에 의한 컨조인트 분석)

  • Lim, Yong B.;Park, Gahee;Chung, Jong Hee
    • Journal of Korean Society for Quality Management
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    • v.45 no.1
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    • pp.55-64
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    • 2017
  • Purpose: A large number of attributes with mixed levels are often considered in the conjoint analysis. The respondents may have difficulty with scoring their preferences accurately because of many attribute items involved in each survey question. We research on the technique for reducing the number of attribute items. Methods: In order to reduce the number of attribute items in a survey question, we make a new attribute by merging two original attributes. A 'No question' option is also included as a new level in a merged attribute. Results: We propose BIB $6^4$ design in the case where we have four attributes with 2 levels and 3 levels, respectively and then analyze all the respondents survey data generated by the repeated simulation study in order to compare various model selection methods. Conclusion: How to reduce the number of attribute items is proposed and how to design and analyze the survey data are illustrated.