2008 IEEE International Conference on Data Mining Workshops最新文献_第10页

Parameter Tuning for Differential Mining of String Patterns 字符串模式差分挖掘的参数调优

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.118

J. Besson, C. Rigotti, I. Mitasiunaite, Jean-François Boulicaut

引用次数: 12

Web Query Prediction by Unifying Model 基于统一模型的Web查询预测

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.53

Ning Liu, Jun Yan, Shuicheng Yan, Weiguo Fan, Zheng Chen

引用次数: 8

A New Graph-Based Algorithm for Clustering Documents 基于图的文档聚类新算法

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.69

Airel Pérez Suárez, José Francisco Martínez Trinidad, J. A. Carrasco-Ochoa, J. Medina-Pagola

引用次数: 6

Multiple-Instance Regression with Structured Data 结构化数据的多实例回归

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.31

K. Wagstaff, T. Lane, A. Roper

引用次数: 31

Speeding up Array Query Processing by Just-In-Time Compilation 通过即时编译加速数组查询处理

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.73

C. Jucovschi, P. Baumann, Sorin Stancu-Mara

引用次数: 12

Actionable Knowledge Discovery for Threats Intelligence Support Using a Multi-dimensional Data Mining Methodology 基于多维数据挖掘方法的威胁情报支持的可操作知识发现

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.78

Olivier Thonnard, M. Dacier

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引用次数: 23

Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets 在高维和噪声数据集中寻找相干共簇

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.20

Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, I. Dhillon

{"title":"Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets","authors":"Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, I. Dhillon","doi":"10.1109/ICDMW.2008.20","DOIUrl":"https://doi.org/10.1109/ICDMW.2008.20","url":null,"abstract":"Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive expressions within a subset of the conditions/features. The existence of a large number of non-informative data points and features makes it challenging to hunt for coherent and meaningful clusters from such datasets. Additionally, since clusters could exist in different subspaces of the feature space, a co-clustering algorithm that simultaneously clusters objects and features is often more suitable as compared to one that is restricted to traditional \"one-sided\" clustering. We propose Robust Overlapping Co-clustering (ROCC), a scalable and very versatile framework that addresses the problem of efficiently mining dense, arbitrarily positioned, possibly overlapping co-clusters from large, noisy datasets. ROCC has several desirable properties that make it extremely well suited to a number of real life applications. Through extensive experimentation we show that our approach is significantly more accurate in identifying biologically meaningful co-clusters in microarray data as compared to several other prominent approaches that have been applied to this task. We also point out other interesting applications of the proposed framework in solving difficult clustering problems.","PeriodicalId":175955,"journal":{"name":"2008 IEEE International Conference on Data Mining Workshops","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129651785","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}

引用次数: 3

Research on Methodology of Classification Mining for Tumor Markers 肿瘤标记物分类挖掘方法研究

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.74

Wei Jiang, Min Yao, Jiekai Yu

引用次数: 0

Co-training by Committee: A New Semi-supervised Learning Framework 委员会共同培训:一种新的半监督学习框架

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.27

Mohamed Farouk Abdel Hady, F. Schwenker

引用次数: 47

Towards Combining Structured Pattern Mining and Graph Kernels 结构化模式挖掘与图核结合的研究

2008 IEEE International Conference on Data Mining Workshops Pub Date : 2008-12-15 DOI: 10.1109/ICDMW.2008.125

Fabrizio Costa, Björn Bringmann

引用次数: 3