Document Type
Closed Project
Publication Date
Spring 2010
Instructor
Charles Weber
Course Title
Knowledge Management
Course Number
ETM 567/667
Subjects
Data mining, Right of privacy, Data protection, Expert systems (Computer science), Knowledge management
Abstract
As individuals engage in daily activities such as shopping, communicating, and interacting with organizations such as health care facilities, financial institutions, or government agencies, data about these activities is constantly being generated, collected, and stored for various reasons. Each person is linked to data records concerning many aspects of his or her life. Some of this data is basically inconsequential and will have limited implications if it falls into the wrong hands. Sometimes benefits can be attained from the collection of this data when individuals are rewarded for being good customers or patrons. However, some information is considered private and we must trust that the organizations that maintain this information will take adequate steps to prevent unauthorized access to this data. This collective data can be used for many purposes, especially when it comes to enhancing decision making. Data mining involves analyzing large stores of data in an attempt to unearth relationships [10]. By uncovering these associations, analysts can increase knowledge in many areas. The potential benefits are endless and can lead to the attainment of information that can save lives and prevent disasters. On the other hand, these same techniques can be used maliciously, with the intent to discriminate. Technologies must be employed that allow for the benefits of data mining to be realized while protecting the privacy of individuals.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
http://archives.pdx.edu/ds/psu/22700
Citation Details
Schenk, Maria, "Preserving Individual Privacy While Implementing Data Mining Techniques" (2010). Engineering and Technology Management Student Projects. 869.
http://archives.pdx.edu/ds/psu/22700
Comments
This project is only available to students, staff, and faculty of Portland State University