Preface This book provides a conceptual and technical introduction to the field of Linked Data. It is intended for anyone who cares about data — using it, managing it, sharing it, interacting with it — and is passionate about the Web. We think this will include data geeks, managers and owners of data sets, system implementors and Web developers. We hope that students and teachers of information management and computer science will find the book a suitable reference point for courses that explore topics in Web development and data management.
Data mining is used wherever there is digital data available today. Notable examples of data mining can be found throughout business, medicine, science, and surveillance.
Privacy concerns and ethics[ edit ] While the term "data mining" itself may have no ethical implications, it is often associated with the mining of information in relation to peoples' behavior ethical and otherwise. A common way for this to occur is through data aggregation. Data aggregation involves combining data together possibly from various sources in a way that facilitates analysis but that also might make identification of private, individual-level data deducible or otherwise apparent.
The threat to an individual's privacy comes into play when the data, once compiled, cause the data miner, or anyone who has access to the newly compiled data set, to be able to identify specific individuals, especially when the data were originally anonymous.
Data may also be modified so as to become anonymous, so that individuals may not readily be identified. This indiscretion can cause financial, emotional, or bodily harm to the indicated individual. In one instance of privacy violation, the patrons of Walgreens filed a lawsuit against the company in for selling prescription information to data mining companies who in turn provided the data to pharmaceutical companies.
Safe Harbor Principles currently effectively expose European users to privacy exploitation by U. As a consequence of Edward Snowden 's global surveillance disclosurethere has been increased discussion to revoke this agreement, as in particular the data will be fully exposed to the National Security Agencyand attempts to reach an agreement have failed.
The HIPAA requires individuals to give their "informed consent" regarding information they provide and its intended present and future uses. More importantly, the rule's goal of protection through informed consent is approach a level of incomprehensibility to average individuals.
Use of data mining by the majority of businesses in the U. Copyright law[ edit ] Situation in Europe[ edit ] Due to a lack of flexibilities in European copyright and database lawthe mining of in-copyright works such as web mining without the permission of the copyright owner is not legal.
Where a database is pure data in Europe there is likely to be no copyright, but database rights may exist so data mining becomes subject to regulations by the Database Directive.
On the recommendation of the Hargreaves review this led to the UK government to amend its copyright law in  to allow content mining as a limitation and exception. Only the second country in the world to do so after Japan, which introduced an exception in for data mining.
However, due to the restriction of the Copyright Directivethe UK exception only allows content mining for non-commercial purposes.
UK copyright law also does not allow this provision to be overridden by contractual terms and conditions. The European Commission facilitated stakeholder discussion on text and data mining inunder the title of Licences for Europe. As content mining is transformative, that is it does not supplant the original work, it is viewed as being lawful under fair use.
For example, as part of the Google Book settlement the presiding judge on the case ruled that Google's digitisation project of in-copyright books was lawful, in part because of the transformative uses that the digitisation project displayed - one being text and data mining.
Data mining and machine learning software. Public access to application source code is also available. Text and search results clustering framework. A chemical structure miner and web search engine. The Konstanz Information Miner, a user friendly and comprehensive data analytics framework.Introduction Join Keith McCormick for an in-depth discussion in this video, Introduction, part of The Essential Elements of Predictive Analytics and Data Mining.
Osmar R. Zaïane, CMPUT Principles of Knowledge Discovery in Databases University of Alberta page 1 Department of Computing Science Chapter I: Introduction to Data Mining We are in an age often referred to as the information age.
Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst.
The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining, sequential pattern mining).
Data mining is the talk of the tech industry, as companies are generating millions of data points about their users and looking for a way to turn that information into increased revenue.
Data mining is a collective term for dozens of techniques to glean information from data and turn it into something meaningful. This article will introduce you to open source data-mining software and some of. Web mining is the application of data mining techniques to discover patterns from the World Wide Web.
As the name proposes, this is information gathered by mining the web. It makes utilization of automated apparatuses to reveal and extricate data from servers and web2 reports, and it permits organizations to get to both organized and.