ICCSA WorkshopsPub Date : 2007-08-26DOI: 10.1109/ICCSA.2007.61
D. Chai, B. Hwang, Eun Hee Kim, Long Jin, K. Ryu
{"title":"Prediction of Frequent Items to One Dimensional Stream Data","authors":"D. Chai, B. Hwang, Eun Hee Kim, Long Jin, K. Ryu","doi":"10.1109/ICCSA.2007.61","DOIUrl":"https://doi.org/10.1109/ICCSA.2007.61","url":null,"abstract":"Data mining in the stream data handles quality and data analysis using extremely large and infinite amount of data and disk or memory with limited volume. In such traditional transaction environment it is impossible to perform frequent items mining because it requires analyzing which item is a frequent one to continuously incoming stream data and which is probable to become a frequent item. This paper proposes a way to predict frequent items using regression model to the continuously incoming one dimensional stream data like the time series data. By establishing the regression model from the stream data, it may be used as a prediction model to uncertain items. The proposing way will exhibit its effectiveness through experiment in stream data.","PeriodicalId":285203,"journal":{"name":"ICCSA Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131456870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICCSA WorkshopsPub Date : 1900-01-01DOI: 10.1109/ICCSA.2009.10
A. Gálvez
{"title":"IFS Matlab Generator: A Computer Tool for Displaying IFS Fractals","authors":"A. Gálvez","doi":"10.1109/ICCSA.2009.10","DOIUrl":"https://doi.org/10.1109/ICCSA.2009.10","url":null,"abstract":"Fractals are among the most exciting and intriguing mathematical objects ever discovered. A particular type of fractals, the Iterated Function Systems (IFS), has received a lot of attention due to its appealing combination of conceptual simplicity, computational efficiency and great ability to reproduce natural formations and complex phenomena. This paper introduces a new Matlab program, called \"IFS Matlab Generator\", for generating and rendering IFS fractals. In addition to providing a gentle introduction to the mathematical basis of IFS, two of the most important rendering algorithms, the deterministic algorithm and the probabilistic algorithm (also called \"chaos game\" algorithm), are briefly outlined. A critical point of chaos game is the choice of the set of probabilities associated with the iterated functions. This issue will be briefly discussed in this paper: we analyze the efficiency of the chaos game algorithm, comparing the standard method for choosing the probabilities proposed by Michael Barnsley with another method based on a new multifractal technique. The latter method optimizes the rendering process by obtaining the most efficient set of probabilities. Some examples aimed at illustrating this technique along with a gallery of beautiful two-dimensional fractal objects are also given.","PeriodicalId":285203,"journal":{"name":"ICCSA Workshops","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131088530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}