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Management Support Systems
Notes Time-Series Databases: Time-series databases contain time related data such stock market
data or logged activities. These databases usually have a continuous flow of new data
coming in, which sometimes causes the need for a challenging real time analysis. Data
mining in such databases commonly includes the study of trends and correlations between
evolutions of different variables, as well as the prediction of trends and movements of the
variables in time. Figure 9.7 shows some examples of time-series data.
Figure 9.7: Examples of Time-Series data
Source: http://webdocs.cs.ualberta.ca/~zaiane/courses/cmput690/notes/Chapter1/
World Wide Web: The World Wide Web is the most heterogeneous and dynamic repository
available. A very large number of authors and publishers are continuously contributing
to its growth and metamorphosis, and a massive number of users are accessing its resources
daily.
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Caution Data in the World Wide Web is organized in inter-connected documents. These
documents can be text, audio, video, raw data, and even applications.
Conceptually, the World Wide Web is comprised of three major components: the content
of the Web, which encompasses documents available; the structure of the Web, which
covers the hyperlinks and the relationships between documents; and the usage of the web,
describing how and when the resources are accessed. A fourth dimension can be added
relating the dynamic nature or evolution of the documents. Data mining in the World
Wide Web, or web mining, tries to address all these issues and is often divided into web
content mining, web structure mining and web usage mining.
9.1.4 Data Mining Functionalities
The kinds of patterns that can be discovered depend upon the data mining tasks employed.
By and large, there are two types of data mining tasks: descriptive data mining tasks that
describe the general properties of the existing data, and predictive data mining tasks that attempt
to do predictions based on inference on available data.
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