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标题：Robust De-anonymization of Large Sparse Datasets
作者：Arvind Narayanan and Vitaly Shmatikov of The University of Texas at Austin
时间：2008年
语言：英语 English
摘要：
"We present a new class of statistical de-nonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge.
We apply our de-anonymization methodology to the Netfix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netfix, the world's largest online movie rental service. We demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. Using the Internet Movie Database as the source of background knowledge, we successfully identified the Netfix records of known users, uncovering their apparent political preferences and other potentially sensitive information."
是否有不完整的部分：完整的论文
Work Cited: http://www.cs.utexas.edu/~shmat/shmat_oak08netflix.pdf/
论文附件：
数据挖掘论文 One.pdf
(686.46 KB, 需要: 1 个论坛币)
第二篇
标题：Fuzzy Set Approaches to Spatial Data Mining of Association Rules
作者：Roy Ladner, Frederick E Petry, and Maria A Cobb
时间：2003年
语言：英语 English
摘要：
"This paper presents an approach to the discovery of association rules for fuzzy spatial data. Association rules provide information of value in assessing siginficant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types, directional or geometric relationships, etc. We have combined and extended techniques developed in both spatial and fuzzy data mining in order to deal with the uncertainty found in typical spatial data."
是否有不完整的部分：完整的论文
Work Cited: http://onlinelibrary.wiley.com/doi/10.1111/1467-9671.00133/abstract
论文附件：
数据挖掘论文 Three.pdf
(193.52 KB, 需要: 1 个论坛币)
第三篇
标题：Research of Data Mining Based on Neural Networks
作者：Xianjun Ni
时间：2008年
语言：英语 English
摘要：
"The application of neural networks in the data mining has become wider. Although neural networks may have complex structure, long training time, and uneasily understandable representation of results, neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining. In this paper the data mining based on neural networks is researched in detail, and the key technology and ways to achieve the data mining based on neural networks are also researched."
是否有不完整的部分：完整的论文
Work Cited: http://www.waset.org/journals/waset/v39/v39-72.pdf
论文附件：
数据挖掘论文 Two.pdf
(322 KB, 需要: 1 个论坛币)
第四篇
标题：Applications of Data Mining Techniques in Pharmaceutical Industry
作者：Jayanthi Ranjan
时间：2005年
语言：英语 English
摘要：
"Almost two decades ago, the information flow in the pharmaceutical industry was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral part of the business processes, the process of transfer of information has become more complicated. Today increasingly technology is being used to help the pharmaceutical firms manage their invetories and to develop new product and services. The implications are such that by a simple process of merging the drug usage and cost of medicines (after completing the legal requirements) with the patient care records of doctors and hospitals helping firms to conduct nation wide trials for its new drugs. Other possible uses of information technology in the field of pharmaceuticals include pricing (two-tier pricing strategy) and exchange of information between vertically integrated drug companies for mutual benefit. Nevertheless, the challenge remains though data collection methods have improved data manipulation techniques are yet to keep pace with them.
Data mining fondly called patterns analysis on large sets of data uses tools like association, clustering, segmentation and classification for helping better manipulation of the data help the pharma firms complete on lower costs while improving the quality of drug discovery and delivery methods. A deep understanding of the knowledge hidden in the Pharma data is vital to a firm's competitive position and organizational decision-making. The paper explains the role of data mining in pharmaceutical industry."
是否有不完整的部分：完整的论文
Work Cited: http://www.jatit.org/volumes/research-papers/Vol3No4/7vol3no4.pdf
论文附件：
数据挖掘论文 Four.pdf
(59.54 KB, 需要: 1 个论坛币)
第五篇
标题：Research Issues in Web Data Mining
作者：Sanjay Madria, Sourav S Bhowmick, W. KNB, E. P. LIM
时间：1999年
语言：英语 English
摘要：
"In this paper, we present an overview of research issues in web mining. We discuss mining with respect to web data referred here as web data mining. In particular, our focus is on web data mining research in context of our web warehousing project called WHOWEDA (Warehouse of Web Data). We have categorized web data mining into three areas: web content mining, web structure mining, and web usage mining. We have highlighted and discussed various research issues involved in each of these web data mining category. We believe that web data mining will be the topic of exploratory research in near future."
是否有不完整的部分：完整的论文
Work Cited: http://dl.acm.org/citation.cfm?id=679137
论文附件：
数据挖掘论文 Five.pdf
(88.15 KB, 需要: 1 个论坛币)
声明：这几篇文章只供学术交流使用，不得用于其他用途。原文所有权利都由原作者保留。如果大家想要引用文章里的任何部分，请联系原作者。谢谢合作。
Announcement: All of these academic research papers only can be used for academic communication rather than any other purposes. These original papers were owned by their authors. If you want to use any part of these papers to write a research paper, please contact original authors. Thanks for your cooperation.
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