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S EQUENTIAL  P ATTERNS & THE GSP A LGORITHM PowerPoint PPT Presentation


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S EQUENTIAL  P ATTERNS & THE GSP A LGORITHM. BY : J OE C ASABONA. I NTRO. What are Sequential Patterns? Why don't ARs suffice? The General Sequential Pattern Algorithm Finding Frequent Sets Candidate Generation Rule Generation. W HAT ARE S EQUENTIAL P ATTERNS ?. - PowerPoint PPT Presentation

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S EQUENTIAL  P ATTERNS & THE GSP A LGORITHM

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S equential p atterns the gsp a lgorithm l.jpg

SEQUENTIAL PATTERNS & THE GSP ALGORITHM

BY: JOE CASABONA


I ntro l.jpg

INTRO

  • What are Sequential Patterns?

  • Why don't ARs suffice?

  • The General Sequential Pattern Algorithm

    • Finding Frequent Sets

    • Candidate Generation

    • Rule Generation


W hat are s equential p atterns l.jpg

WHATARE SEQUENTIAL PATTERNS?

"Finding statistically relevant patterns between data examples where the values are delivered in a sequence." [3]

Very similar to Association Rules, but sequence in this case matters.

There may be times when order is important. 


S equential p attern e xamples l.jpg

SEQUENTIAL PATTERN EXAMPLES

In Transaction Processing: 

    Do customers usually buy a new controller or a game first after buying an Xbox?

In Text Mining:

    Order of the words important for finding linguistic or

language patterns [1]


O bjective l.jpg

OBJECTIVE

Given a set S of input data sequences, find all sequences that have a user-specified minimum support. This is called a 'frequent sequence' or sequential pattern. [1]

We will use the Generalized Sequential Pattern Algorithm (GSP)


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GSP

Similar to Apriori Algorithm

  •  Find individual items with minSupport (1-sequences)

  • Use them to find 2-sequences

  • Continue using k-sequences to find (k+1)-sequences

  • Stop when there are no more frequent sequences.

    Difference is in Candidate Generation 


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GSP: CANDIDATE GENERATION

Input : Frequent Set k-1 (F[k-1])

Output: Candidate Set C[k]

How it works:

  • Join F[k-1] with F[k-1]

  •  Get rid of infrequent sequences (prune)

  • Note: Order of items matter 


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CANDIDATE EXAMPLE

F[3] = <{1, 2} {4}>, <{1, 2} {5}>, <{1} {4, 5}>, <{1, 4} {6}>, <{2} {4, 5}>, <{2} {4} {6}>

After Join: <{1, 2} {4, 5}>, <{1, 2} { 4} {6}>

After Prune: <{1, 2} {4, 5}> 

C[4]=  <{1, 2} {4, 5}>


R ule g eneration l.jpg

RULE GENERATION

Objective not to generate rules, but it can be done. 

Sequential Rule: Apply confidence to  Frequent Sequences

Label Sequential Rules: Replace some elements in X with *


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RERERENCES

[1] The Book I am using:

 Liu, Bing. Web Data Mining, Chapter 2: Association Rules and Sequential Patterns. Springer, December, 2006 

Wikipedia:

[2] "GSP Algorithm." http://en.wikipedia.org/wiki/GSP_AlgorithmJune 3, 2008

[3] "Sequence Mining." http://en.wikipedia.org/wiki/Sequence_miningOct. 30, 2008