• Title/Summary/Keyword: Pattern Mining

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Frequent Items Mining based on Regression Model in Data Streams (스트림 데이터에서 회귀분석에 기반한 빈발항목 예측)

  • Lee, Uk-Hyun
    • The Journal of the Korea Contents Association
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    • v.9 no.1
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    • pp.147-158
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    • 2009
  • Recently, the data model in stream data environment has massive, continuous, and infinity properties. However the stream data processing like query process or data analysis is conducted using a limited capacity of disk or memory. In these environment, the traditional frequent pattern discovery on transaction database can be performed because it is difficult to manage the information continuously whether a continuous stream data is the frequent item or not. In this paper, we propose the method which we are able to predict the frequent items using the regression model on continuous stream data environment. We can use as a prediction model on indefinite items by constructing the regression model on stream data. We will show that the proposed method is able to be efficiently used on stream data environment through a variety of experiments.

Design of a Product Recommender based on Web Log Analysis (웹 로그 분석에 기반한 상품 추천기의 설계)

  • 김건량;이도헌
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2000.10a
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    • pp.349-352
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    • 2000
  • As a lot of people have used electronic commerce, many shopping malls have appeared on the Interne and the shopping information in them has been enormous. So, the need for a system to recommend product to customers is on the increase so as to reduce time and efforts for shopping. In this paper, we suppose a Product Recommender System which is constructed by applying data mining techniques to web for files and analyzing customer's action pattern, customer's profile and product purchase data. This system offers convenience that customers can get their desired information easily, by sending e-mail or mail and recommending web pages when they visit a shopping mall.

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CANCER CLASSIFICATION AND PREDICTION USING MULTIVARIATE ANALYSIS

  • Shon, Ho-Sun;Lee, Heon-Gyu;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.706-709
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    • 2006
  • Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

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Emotion Prediction of Document using Paragraph Analysis (문단 분석을 통한 문서 내의 감정 예측)

  • Kim, Jinsu
    • Journal of Digital Convergence
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    • v.12 no.12
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    • pp.249-255
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    • 2014
  • Recently, creation and sharing of information make progress actively through the SNS(Social Network Service) such as twitter, facebook and so on. It is necessary to extract the knowledge from aggregated information and data mining is one of the knowledge based approach. Especially, emotion analysis is a recent subdiscipline of text classification, which is concerned with massive collective intelligence from an opinion, policy, propensity and sentiment. In this paper, We propose the emotion prediction method, which extracts the significant key words and related key words from SNS paragraph, then predicts the emotion using these extracted emotion features.

A Study on the Precipitates in Rapidly Solidified Al-(Fe, Ce) Alloys by Analysis of X-Ray Diffraction (급냉응고된 Al-(Fe, Ce) 합금에서 형성되는 석출상의 X-선적연구)

  • Park, Ik-Min;Lee, Kyu-Han;Choe, Jeong-Cheol;Jo, Hyung-Ho
    • Journal of Korea Foundry Society
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    • v.8 no.4
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    • pp.446-452
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    • 1988
  • To obtain detailed information on the metastable and the equilibrium phases in rapidly solidified Al-(Fe,Ce) alloys, analysis of X-ray diffraction pattern has been carried out. It has been found that the metastable phase formed in Al-Fe alloys including up to 6wt%Fe is $Al_6Fe$ and the equilibrium phase is $Al_3Fe$. Any X-ray diffraction peak corresponding to the equilibrium phase $Al_{13}Fe_4$ has not been observed during aging. In Al-4wt%Fe alloy, which is ribbon shape with thickness less than $70\;{\mu}m$, aged at $400^{\circ}C$ for 1h after rapid solidification, unidentified phase has been found. In Al-4wt%Ce alloy, only X-ray diffraction peak corresponding to the equilibrium phase, $Al_4Ce$ has been observed. It has been found that the metastable phase Formed in Al-Fe-Ce alloys including up to 6wt% Fe and 4wt% Ce is $Al_6Fe$ and the equilibrium phases are $Al_3Fe$ and $Al_{10}CeFe_2$.

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Prediction of the Major Factors for the Analysis of the Erosion Effect on Atomic Oxygen in LEO Satellite Using a Machine Learning Method (LSTM)

  • Kim, You Gwang;Park, Eung Sik;Kim, Byung Chun;Lee, Suk Hoon;Lee, Seo Hyun
    • Journal of Aerospace System Engineering
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    • v.14 no.2
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    • pp.50-56
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    • 2020
  • In this study, we investigated whether long short-term memory (LSTM) can be used in the future to predict F10.7 index data; the F10.7 index is a space environment factor affecting atomic oxygen erosion. Based on this, we compared the prediction performances of LSTM, the Autoregressive integrated moving average (ARIMA) model (which is a traditional statistical prediction model), and the similar pattern searching method used for long-term prediction. The LSTM model yielded superior results compared to the other techniques in the prediction period starting from the max/min points, but presented inferior results in the prediction period including the inflection points. It was found that efficient learning was not achieved, owing to the lack of currently available learning data in the prediction period including the maximum points. To overcome this, we proposed a method to increase the size of the learning samples using the sunspot data and to upgrade the LSTM model.

Experimental studies on mass transport in groundwater through fracture network using artificial fracture model

  • Tsuchihara Takeo;Yoshimura Masahito;Ishida Satoshi;Imaizumi Masayuki;Ohonishi Ryouichi
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.676-683
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    • 2003
  • A laboratory experiment using artificial fracture rocks was used to understand the 3-dimensional dispersion of a tracer and the mixing process in a fractured network. In this experiment, 12cm polystyrene foam cubes with two electrodes for monitoring electric conductivity (EC) were used as artificial fractured rocks. Distilled water with 0.5mS/m was used as a tracer in water with 35mS/m and the difference of EC between the tracer and the water was monitored by a multipoint simultaneous measurement system of electrical resistance. The results showed that even if the fracture arrangement pattern was not straight in the direction of the flow, the tracer did not diffuse along individual fractures and an oval tracer plume, which was the distribution of tracer concentrations, tended to be form in the direction of the flow. The vertical cross section of the tracer distribution showed small diffusivity in the vertical direction. The calculated total tracer volume passing through each measurement point in the horizontal cross section showed while that the solute passed through measurement points near the direction of hydraulic gradient and in other directions, the passed tracer volumes were small. Using Peclet number as a criterion, it was found that the mass distribution at the fracture intersection was controlled in the stage of transition between the complete mixing model and the streamline routing model.

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A Study of Authorized Stockage List Selection using Market Basket Analysis (장바구니 분석을 활용한 ASL 선정 연구)

  • Choi, Myoung-Jin
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.2
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    • pp.163-172
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    • 2012
  • In this study, It is assumed that customers are both usage unit of spare parts and stores of displaying and selling the goods that are installation unit of having the spare parts. The demand pattern through the effective order of spare parts and issue list in installation unit is investigated based on the assumption. Current ASL (Authorized Stockage List) selection of the army has been conducted in the way of using the analysis result of real usage experiences on spare parts used during the Korea War. For this study, ASL selection criteria and procedures based on army regulations and field manuals are specified. Since the traditional method does not presents the association analysis on spare parts used for the current equipment operating and does not have the clear criterion and analysis system about the ASL selection, in order to solve these problems, it was carried out that the association rule is employed for analyzing relationship between the effective order and issue list of the spare parts in point of the spare parts between usage unit and occurring month about purchase spare parts based on the star-schema table. Finally the new ASL selection way using the analysis result is proposed.

A Study on Efficient Learning Units for Behavior-Recognition of People in Video (비디오에서 동체의 행위인지를 위한 효율적 학습 단위에 관한 연구)

  • Kwon, Ick-Hwan;Hadjer, Boubenna;Lee, Dohoon
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.196-204
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    • 2017
  • Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

A Design of Goods Recommendation System based on Multi-crossselling (다중크로스셀링 기반의 개인 상품 추천 시스템의 설계)

  • Yun Jong-Chan;Kim Jong-Jin;Youn Sung-Dae
    • Journal of Korea Multimedia Society
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    • v.9 no.9
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    • pp.1095-1106
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    • 2006
  • Recently, many effort is demanded for appropriate operation and management of the Electronic commerce system. Electronic commerce system must provide information satisfying customers. To do this, many kinds of studies are being advanced about electronic commerce system using intelligent agent technology. In this paper, We propose a support system for goods based on Case-Based Reasoning(CBR) and multi-crossselling technology. The system can supply the information of goods that is suitable about customer need under specification condition with CBR technique and can search several goods approximate to customer pattern using Multi-crossselling technique.

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