Question

Describe the difficulties of mining a huge amount of data (such as billions of tuples) in comparison with mining a small amount of data (such as a few hundred tuples data se

Answer 1

Answer:

Challenges to data mining regarding data mining methodology and user interaction issues include the following: 1.mining different kinds of knowledge in databases, 2.interactive mining of knowledge at multiple levels of abstraction, 3.incorporation of background knowledge, Data mining query languages and ad hoc data mining,presentation and visualization of data mining results, handlingnoisy or incomplete data, and pattern evaluation. Below are the descriptions of the first three challenges arementioned:1)Mining different kinds of knowledge in databases: Differentusers are interested in different kinds of knowledge and willrequire a wide range of data analysis and knowledge discoverytasks such as data characterization, discrimination, association,classification, clustering, trend and deviation analysis, andsimilarity analysis. Each of these tasks will use the same databasein different ways and will require different data mining techniques.2)Interactive mining of knowledge at multiple levels ofabstraction: Interactive mining, with the use of OLAP operationson a data cube, allows users to focus the search for patterns,providing and refining data mining requests based on returnedresults. The user can then interactively view the data and discoverpatterns at multiple granularities and from different angles.3)Incorporation of background knowledge: Backgroundknowledge, or information regarding the domain under study suchas integrity constraints and deduction rules, may be used to guidethe discovery process and allow discovered patterns to beexpressed in concise terms and at different levels of abstraction.This helps to focus and speed up a data mining process or judgethe interestingness of discovered patterns.

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