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What is Data Mining Trends and Research Frontiers?

Data mining is the process of analyzing a large size of information to find out the patterns, trends. It can be used for corporations to find out about customers’ choices, make a good relationship with customers, increase the revenue, reduce risks. Data mining is based on complex algorithms that allow data segmentation to discover numerous trends and patterns, detect deviations, and estimate the likelihood of certain occurrences occurring. Raw data can be in both analog and digital formats, and it is essentially dependent on the data’s source. Companies must keep up with the latest data mining trends and stay current in order to succeed in the industry and beat out the competition.

Types of Mining Sequence in Data Mining:

1. Mining Time Series

A specified number of data points are recorded at a specific time or events obtained over repeated measurements of time in a mining time series. The values or data are typically measured in equal time intervals like- hourly, weekly, daily. In time-series data is also recorded regular intervals or characteristic time-series components are trend, seasonal, cycle, irregular.



Application of Time Series:

Time Series Analysis Methods:



2. Mining Symbolic Sequence

A symbolic sequence is made up of an ordered list of elements that can be recorded with or without a sense of time. This sequence can be used in a variety of ways, including consumer shopping sequences, web clickstreams, software execution sequences, biological sequences, and so on.

Mining of sequential patterns entails identifying the subsequences that appear frequently in one or more sequences. As a result of substantial research in this area, a number of scalable algorithms have been developed. Alternatively, we can only mine the set of closed sequential patterns, where a sequential pattern s is closed if it is a correct subsequence of s’ and s’ has the same support as s.

For example:

if  where a, b, c, d and e are items, then S is a subsequence of S’.

3. Mining Biological Sequence

Biological sequences are made up of nucleotide or amino acid sequences. In bioinformatics and modern biology, biological sequence analysis compares, aligns, indexes, and analyzes biological sequences. Biological sequences analysis plays a crucial role in bioinformatics and modern biology. Such analysis can be partitioned into two tasks- pairwise sequence alignment and multiple sequence alignment. 

Biological Sequence Methods:

Application of Data Mining: 

Trends of Data Mining: 

Article Tags :
Data Mining
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