Nowadays Data Mining and knowledge discovery are evolving a crucial technology for business and researchers in many domains.Data Mining is developing into established and trusted discipline, many still pending challenges have to be solved.
Some of these challenges are given below.
- Security and Social Challenges:
Decision Making strategies is done through data collection sharing, so it requires considerably security.Private information about individuals and sensitive information are collected for customers profiles, user behavior pattern understanding. Illegal access to information and confidential nature of information becoming an important issue.
- User Interface:
The knowledge discovered is discovered using data mining tools is useful only if it is interesting and above all understandable by user.From good visualization interpretation of data mining results can be eased and helps better understand their requirements. To obtain good visualization many research is carried out for big data sets that display and manipulate mined knowledge.
- Mining Methodology Challenges:
These challenges are related to data mining approaches and their limitations. Mining approaches that cause problem are:
(i) Versatility of the mining approaches, (ii) Diversity of data available, (iii) Dimensionality of the domain, (iv) Control and handling of noise in data, etc.
Different approaches may implement differently based upon data consideration. Some algorithms requires noise-free data.Mostly data sets contain exceptions, invalid or incomplete information lead to complication in the analysis process and in some cases compromise the precision of the results.
- Complex Data:
Real world data is actually heterogeneous and it could be multimedia data containing images, audio and video, complex data, temporal data, spatial data, time series, natural language text etc. It is difficult to handle these various kinds of data and extract required information. New tools and methodologies is developing to extract relevant information.
The performance of the data mining system basically depends on the efficiency of algorithms and techniques are using. The algorithms and techniques designed are not up to the mark lead to affect the performance of the data mining process.
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