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Sequential Patterns Wen-Chih Peng ( 彭文志 ) Dept. of Computer Science National Chiao-Tung University
Sequence Data Sequence Database: Object Timestamp Events A 10 2, 3, 5 A 20 6, 1 A 23 1 B 11 4, 5, 6 B 17 2 B 21 7, 8, 1, 2 B 28 1, 6 C 14 1, 8, 7
Examples of Sequence Data Sequence E1 E2 E1 E3 E2 E3 E4 E2 Element (Transaction) Event  (Item) Bases A,T,G,C An element of the DNA sequence  DNA sequence of a particular species Genome sequences Types of alarms generated by sensors  Events triggered by a sensor at time t History of events generated by a given sensor Event data Home page, index page, contact info, etc A collection of files viewed by a Web visitor after a single mouse click Browsing activity of a particular Web visitor Web Data Books, diary products, CDs, etc A set of items bought by a customer at time t Purchase history of a given customer Customer Event (Item) Element (Transaction) Sequence Sequence Database
Formal Definition of a Sequence ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Examples of Sequence ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Formal Definition of a Subsequence ,[object Object],[object Object],[object Object],< {2,4} {2,4} {2,5} > < {1,2} {3,4} >  < {2,4} {3,5,6} {8} > Data sequence Yes < {2} {4} > No < {1} {2} > Yes < {2} {3,5} > Contain? Subsequence
What Is Sequential Pattern Mining? ,[object Object],A  sequence database   A  sequence  : < (ef) (ab)  (df) c b > An element may contain a set of items. Items within an element are unordered and we list them alphabetically.   <a(bc)dc> is a  subsequence  of  < a (a bc )(ac) d ( c f)> Given  support threshold   min_sup  =2, <(ab)c> is a  sequential pattern <eg(af)cbc> 40 <(ef)( ab )(df) c b> 30 <(ad)c(bc)(ae)> 20 <a( ab c)(a c )d(cf)> 10 sequence SID
Sequential Pattern Mining: Definition ,[object Object],[object Object],[object Object],[object Object],[object Object]
Extracting Sequential Patterns ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Sequential Pattern Mining: Challenge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Mining Sequential Patterns ,[object Object],[object Object],[object Object],[object Object],[object Object]
Sequential Patterns (cont’d) ,[object Object],[object Object],[object Object]
Algorithm ,[object Object],[object Object],[object Object],[object Object]
Algorithm (cont’d) ,[object Object],[object Object],[object Object],[object Object]
Original Database
Sort Phase
Customer-Sequence Version  of the Database
Large itemset Phase (support:2)
Transformation Phase
Sequence Phase ,[object Object],[object Object],2 <2 3 4> 2 <1 3 5> 3 <1 3 4>  2 <1 2 4> 2 <1 2 3> Support Sequence <1 3 5 4> <1 3 4 5> <1 2 4 3> <1 2 3 4>
<{1 5} {2} {3} {4}> <{1} {3} {4} {3 5}> <{1} {2} {3} {4}> <{1} {3} {5}> <{4} {5}> Customer Sequences Sequence Support <1> 4 <2> 2 <3> 4 <4> 4 <5> 4 Large 1-Sequences Sequence Support <1 2> 2 <1 3> 4 <1 4> 3 <1 5> 2 <2 3> 2 <2 4> 2 <3 4> 3 <3 5> 2 <4 5> 2 Large 2-Sequences Sequence Support <1 2 3> 2 <1 2 4> 2 <1 3 4> 3 <1 3 5> 2 <2 3 4> 2 Large 3-Sequences Sequence Support <1 2 3 4> 2 Large 4-Sequences Sequence Support <1 2 3 4> 2 <1 3 5> 2 <4 5> 2 Maximal Large Sequences
Maximal Sequence ,[object Object],[object Object],[object Object]
Sequential Patterns With support > 25% < (30) (90) > < (30) (40 70) > The answer set
Notes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Rule Discovery from Time Sequences ,[object Object],[object Object],[object Object],[object Object],[object Object]
Episode Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],E B A F B A C
Example of Episode Mining  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],0  10  20  30  40  50  60  70  80  90  100  110  120 130 140  150 D  C  A  B  D  A  B  C  A  D  C  A  B  D  A
Event Sequence ,[object Object],[object Object]
Sliding Window ,[object Object],[object Object],0  10  20  30  40  50  60  70  80  90 D  C  A  B  D  A  B  C
Frequency of an Episode ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Find Frequent Episodes ,[object Object],[object Object],[object Object],[object Object]
FreeSpan ,[object Object],[object Object],[object Object],[object Object]
Example of FreeSpan f_list = a: 4 ,b: 4 ,c: 4 ,d: 3 ,e: 3 ,f: 3 g is deleted because of support of g <2 . Example database: min support = 2 <eg(af)cbc> 40 <(ef)(ab)(df)cb> 30 <(ad)c(bc)(ae)> 20 <a(abc)(ac)d(cf)> 10 Sequence Sequence id
Example of FreeSpan (cont’d) ,[object Object],Frequent Patterns <a> <aa> => {a}-projected database <e( a f)cbc> 40 <(ef)( a b)(df)cb> 30 <( a d)c(bc)( a e)> 20 < a ( a bc)( a c)d(cf)> 10 Sequence Sequence id <a> 40 <a> 30 <aa> 20 <aaa> 10
Example of FreeSpan (cont’d) ,[object Object],Frequent Patterns <b> <ab> <ba> <(ab)> => {b}-projected database <e( a f)c b c> 40 <(ef)( ab )(df)c b > 30 <( a d)c( b c)( a e)> 20 < a ( ab c)( a c)d(cf)> 10 Sequence Sequence id <ab> 40 <(ab)b> 30 <aba> 20 <a(ab)a> 10
Example of FreeSpan (cont’d) ,[object Object],Frequent Patterns <c> <ac> <bc> <(bc)> <ca> <cb> <(ab)c> <acc> <acb> => {c}-projected database <e( a f) cbc > 40 <(ef)( ab )(df) cb > 30 <( a d) c ( bc )( a e)> 20 < a ( abc )( ac )d( c f)> 10 Sequence Sequence id <acbc> 40 <(ab)cb> 30 <ac(bc)a> 20 <a(abc)(ac)c> 10
PrefixSpan ,[object Object],[object Object],[object Object]
PrefixSpan - Concepts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
PrefixSpan – Concepts ,[object Object],[object Object],[object Object],[object Object]
Example of PrefixSpan <a>-projected database By scanning <a>-projected database once, all the length-2 sequential patterns having prefix <a> can be found. <aa>:2  <ab>:4  <(ab)>:2  <ac>:4  <ad>:2  <af>:2 Recursively, patterns with prefix <a> can be partitioned into 6 subsets. => <e( a f)cbc > 40 <(ef)( a b)(df)cb > 30 <( a d)c(bc)(ae )> 20 < a (abc)(ac)d(cf) > 10 Sequence Sequence id <(_f)cbc> 40 <(_b)(df)cb> 30 <(_d)c(bc)(ae)> 20 <(abc)(ac)d(cf)> 10
Example of PrefixSpan (cont’d) < aa >-projected database => < ab >-projected database => Sequential patterns of <ab>-projected db: <(_c)>,<(_c)a>,<a><c> <(_f)c b c> 40 <(_b)(df)cb> 30 <(_d)c( b c)( a e)> 20 <( a b c)(ac)d(cf)> 10 Sequence Sequence id <c> 40 <(_c)(ae)> 20 <(_c)(ac)d(cf)> 10 <(_e)> 20 <(_bc)(ac)d(cf)> 10
Example of PrefixSpan (cont’d) <b>-projected database Sequential patterns <b> <ba> <bc> <(bc)> <(bc)a> <bd> <bdc> <bf> => <e(af)c b c > 40 <(ef)(a b )(df)cb > 30 <(ad)c( b c)(ae )> 20 <a(a b c)(ac)d(cf)> 10 Sequence Sequence id <c> 40 <(df)cb> 30 <(_c)(ae)> 20 <(_c)(ac)d(cf)> 10
References ,[object Object],[object Object],[object Object]
References (cont’d) ,[object Object],[object Object],[object Object],[object Object]
References (cont’d) ,[object Object],[object Object],[object Object]
References (cont’d) ,[object Object],[object Object],[object Object]
References (cont’d) ,[object Object],[object Object],[object Object],[object Object]

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03

  • 1. Sequential Patterns Wen-Chih Peng ( 彭文志 ) Dept. of Computer Science National Chiao-Tung University
  • 2. Sequence Data Sequence Database: Object Timestamp Events A 10 2, 3, 5 A 20 6, 1 A 23 1 B 11 4, 5, 6 B 17 2 B 21 7, 8, 1, 2 B 28 1, 6 C 14 1, 8, 7
  • 3. Examples of Sequence Data Sequence E1 E2 E1 E3 E2 E3 E4 E2 Element (Transaction) Event (Item) Bases A,T,G,C An element of the DNA sequence DNA sequence of a particular species Genome sequences Types of alarms generated by sensors Events triggered by a sensor at time t History of events generated by a given sensor Event data Home page, index page, contact info, etc A collection of files viewed by a Web visitor after a single mouse click Browsing activity of a particular Web visitor Web Data Books, diary products, CDs, etc A set of items bought by a customer at time t Purchase history of a given customer Customer Event (Item) Element (Transaction) Sequence Sequence Database
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  • 17. Customer-Sequence Version of the Database
  • 18. Large itemset Phase (support:2)
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  • 21. <{1 5} {2} {3} {4}> <{1} {3} {4} {3 5}> <{1} {2} {3} {4}> <{1} {3} {5}> <{4} {5}> Customer Sequences Sequence Support <1> 4 <2> 2 <3> 4 <4> 4 <5> 4 Large 1-Sequences Sequence Support <1 2> 2 <1 3> 4 <1 4> 3 <1 5> 2 <2 3> 2 <2 4> 2 <3 4> 3 <3 5> 2 <4 5> 2 Large 2-Sequences Sequence Support <1 2 3> 2 <1 2 4> 2 <1 3 4> 3 <1 3 5> 2 <2 3 4> 2 Large 3-Sequences Sequence Support <1 2 3 4> 2 Large 4-Sequences Sequence Support <1 2 3 4> 2 <1 3 5> 2 <4 5> 2 Maximal Large Sequences
  • 22.
  • 23. Sequential Patterns With support > 25% < (30) (90) > < (30) (40 70) > The answer set
  • 24.
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  • 33. Example of FreeSpan f_list = a: 4 ,b: 4 ,c: 4 ,d: 3 ,e: 3 ,f: 3 g is deleted because of support of g <2 . Example database: min support = 2 <eg(af)cbc> 40 <(ef)(ab)(df)cb> 30 <(ad)c(bc)(ae)> 20 <a(abc)(ac)d(cf)> 10 Sequence Sequence id
  • 34.
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  • 40. Example of PrefixSpan <a>-projected database By scanning <a>-projected database once, all the length-2 sequential patterns having prefix <a> can be found. <aa>:2 <ab>:4 <(ab)>:2 <ac>:4 <ad>:2 <af>:2 Recursively, patterns with prefix <a> can be partitioned into 6 subsets. => <e( a f)cbc > 40 <(ef)( a b)(df)cb > 30 <( a d)c(bc)(ae )> 20 < a (abc)(ac)d(cf) > 10 Sequence Sequence id <(_f)cbc> 40 <(_b)(df)cb> 30 <(_d)c(bc)(ae)> 20 <(abc)(ac)d(cf)> 10
  • 41. Example of PrefixSpan (cont’d) < aa >-projected database => < ab >-projected database => Sequential patterns of <ab>-projected db: <(_c)>,<(_c)a>,<a><c> <(_f)c b c> 40 <(_b)(df)cb> 30 <(_d)c( b c)( a e)> 20 <( a b c)(ac)d(cf)> 10 Sequence Sequence id <c> 40 <(_c)(ae)> 20 <(_c)(ac)d(cf)> 10 <(_e)> 20 <(_bc)(ac)d(cf)> 10
  • 42. Example of PrefixSpan (cont’d) <b>-projected database Sequential patterns <b> <ba> <bc> <(bc)> <(bc)a> <bd> <bdc> <bf> => <e(af)c b c > 40 <(ef)(a b )(df)cb > 30 <(ad)c( b c)(ae )> 20 <a(a b c)(ac)d(cf)> 10 Sequence Sequence id <c> 40 <(df)cb> 30 <(_c)(ae)> 20 <(_c)(ac)d(cf)> 10
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