SEQUENTIAL PATTERNS THE GSP ALGORITHM BY JOE CASABONA

SEQUENTIAL PATTERNS & THE GSP ALGORITHM BY: JOE CASABONA

INTRO a. What are Sequential Patterns? b. Why don't ARs suffice? c. The General Sequential Pattern Algorithm a. Finding Frequent Sets b. Candidate Generation c. Rule Generation

WHAT ARE 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.

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]

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)

GSP Similar to Apriori Algorithm a. Find individual items with min. Support (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
![GSP: CANDIDATE GENERATION Input : Frequent Set k-1 (F[k-1]) Output: Candidate Set C[k] How GSP: CANDIDATE GENERATION Input : Frequent Set k-1 (F[k-1]) Output: Candidate Set C[k] How](http://slidetodoc.com/presentation_image_h2/5f9cc04790c4e2546a77d62afa807ca3/image-7.jpg)
GSP: CANDIDATE GENERATION Input : Frequent Set k-1 (F[k-1]) Output: Candidate Set C[k] How it works: a. Join F[k-1] with F[k-1] • Get rid of infrequent sequences (prune) • Note: Order of items matter
![CANDIDATE EXAMPLE F[3] = <{1, 2} {4}>, <{1, 2} {5}>, <{1} {4, 5}>, <{1, CANDIDATE EXAMPLE F[3] = <{1, 2} {4}>, <{1, 2} {5}>, <{1} {4, 5}>, <{1,](http://slidetodoc.com/presentation_image_h2/5f9cc04790c4e2546a77d62afa807ca3/image-8.jpg)
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}>

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 *
![RERERENCES [1] The Book I am using: Liu, Bing. Web Data Mining, Chapter 2: RERERENCES [1] The Book I am using: Liu, Bing. Web Data Mining, Chapter 2:](http://slidetodoc.com/presentation_image_h2/5f9cc04790c4e2546a77d62afa807ca3/image-10.jpg)
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_Algorithm June 3, 2008 [3] "Sequence Mining. " http: //en. wikipedia. org/wiki/Sequence_mining Oct. 30, 2008
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