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Titlebook: Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects; 8th Industrial Confe Petra Perner Conference

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發(fā)表于 2025-3-21 16:27:47 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
期刊簡稱8th Industrial Confe
影響因子2023Petra Perner
視頻videohttp://file.papertrans.cn/148/147670/147670.mp4
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects; 8th Industrial Confe Petra Perner Conference
影響因子ICDM / MLDM Medaillie (limited edition) Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia ICDM 2008 was the eighth event of the Industrial Conference on Data Mining held in Leipzig (www.data-mining-forum.de). For this edition the Program Committee received 116 submissions from 20 countries. After the peer-review process, we accepted 36 high-quality papers for oral presentation, which are included in these proceedings. The topics range from aspects of classification and prediction, clustering, Web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Thirteen papers were selected for poster presentations that are published in the ICDM Poster Proceeding Volume. In conjunction with ICDM there were three workshops focusing on special hot application-oriented topics in data mining. The workshop Data Mining in Life Science DMLS 2008 was held the third time this year and the workshop Data Mining in Marketing DMM 2008 ran for the second time this year. Additionally, we introduced an International Workshop on Case-Based Reasoning for Multimedia Data CBR-MD.
Pindex Conference proceedings 2008
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書目名稱Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects影響因子(影響力)




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沙發(fā)
發(fā)表于 2025-3-22 00:18:46 | 只看該作者
Additive and Abelian Categories,rom cheaply-available in-season data. Once this prediction is possible, the industrial application is quite straightforward: use data mining with neural networks for, e.g., optimizing fertilizer usage, in economic or environmental terms.
板凳
發(fā)表于 2025-3-22 03:16:27 | 只看該作者
Complexes in Additive Categories, concept. These descriptions can be interpreted as explanations of groups of melanomas. Experiments prove that explanations are very useful for experts to reconsider the characterization of melanoma classes.
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發(fā)表于 2025-3-22 05:19:26 | 只看該作者
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發(fā)表于 2025-3-22 12:42:21 | 只看該作者
Categories for Software Engineeringings. Our methodology follows an Apriori approach [9] and avoids pre and post processing as opposed to most weighted association rule mining algorithms, thus eliminating the extra steps during rules generation. The paper concludes with experimental results and discussion on evaluating the proposed approach.
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發(fā)表于 2025-3-22 14:16:07 | 只看該作者
Categories for Software Engineering different types of Na?ve Bayes classifier. The results obtained from the experiments carried out show the relevance of choosing an appropriate feature selection technique in order to obtain the most accurate results.
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發(fā)表于 2025-3-22 18:04:23 | 只看該作者
Conference proceedings 2008 the Industrial Conference on Data Mining held in Leipzig (www.data-mining-forum.de). For this edition the Program Committee received 116 submissions from 20 countries. After the peer-review process, we accepted 36 high-quality papers for oral presentation, which are included in these proceedings. T
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發(fā)表于 2025-3-23 00:32:49 | 只看該作者
Complexes in Abelian Categories, an integrated environment for mining clinical data acquired by different media. In particular, focus is herein given to the infrastructure of the warehouse and its current functionalities not limited to storage and management but including intelligent representation and annotation of multimedia objects.
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發(fā)表于 2025-3-23 04:59:02 | 只看該作者
Complexes in Abelian Categories,the approach computational experiment involving several benchmark datasets has been carried out. Experiment results show that using GEP-induced expression trees as weak classifiers allows for construction of a high quality ensemble classifier outperforming, in terms of classification accuracy, many other recently published solutions.
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發(fā)表于 2025-3-23 05:40:47 | 只看該作者
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