## What is sequential patterns in data mining?

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Sequential patterns are frequent patterns that are available in one or several successive transactions of many input sequences. Due to its scalability, the PrefixSpan algorithm is used for sequential patterns mining. Usually, the market basket analysis runs on a large fact table or on a part of it.

**What is sequential rule mining?**

Sequential Rule Mining is a data mining technique which consists of discovering rules in sequences. Sequential Rule Mining has many applications for example for analysing the behaviour of customers in supermarkets or users on a website or passengers at an airport.

### What is PrefixSpan algorithm?

PrefixSpan (Prefix-projected Sequential pattern mining) algorithm is very well known algorithm for sequential data mining. It extracts the sequential patterns through pattern growth method. The algorithm performs very well for small datasets.

**What is pattern mining?**

Pattern mining concentrates on identifying rules that describe specific patterns within the data. Market-basket analysis, which identifies items that typically occur together in purchase transactions, was one of the first applications of data mining.

#### What is the difference between association rule mining and sequential pattern mining?

You might have heard of association rule mining (ARM) which allows you to generate association rules to display the relationships between items in a dataset. Sequence pattern mining is applicable for datasets that have a time-related format and can be used to develop marketing or campaign strategies.

**What is a sequential data mining mention two examples of sequential mining?**

Typical examples include customer shopping sequences, Web clickstreams, bio- logical sequences, sequences of events in science and engineering, and in natural and social developments. In this section, we study sequential pattern mining in transactional databases.

## How is mining sequence patterns from transactional data is performed?

Sequential pattern mining is trying to find relationships between occurrences of sequential events, to find if there exists any specific order of the occurrences. We can find the sequential patterns of specific individual items also we can find the sequential patterns across different items.

**What is the sequence pattern?**

A sequence or number pattern is an ordered set of numbers or diagrams that follow a rule. A term is a number or diagram in a sequence. A sequence can be described on a term-to-term basis or position to term. A formula can be used to calculate the term of a sequence when given its position number.

### What is sequence data?

What is sequential data? Whenever the points in the dataset are dependent on the other points in the dataset the data is said to be Sequential data. A common example of this is a Timeseries such as a stock price or a sensor data where each point represents an observation at a certain point in time.

**What is the length of sequential pattern?**

Each candidate sequence contains one more item than a seed sequential pattern, where each element in the pattern may contain one item or multiple items. The number of items in a sequence is called the length of the sequence.

#### What is spade algorithm?

An algorithm to Frequent Sequence Mining is the SPADE (Sequential PAttern Discovery using Equivalence classes) algorithm. It uses a vertical id-list database format, where we associate to each sequence a list of objects in which it occurs.