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ORDER INDEPENDENTINCREMENTAL EVOLVING FUZZY GRAMMAR FRAGMENT LEARNER
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ORDER INDEPENDENT INCREMENTAL EVOLVING FUZZY GRAMMAR FRAGMENT LEARNER

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ISDA 09

ISDA 09

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  • Minimal Combination for Incremental Grammar Fragment Learning-IFSA/EUFSLAT 2009 Minimal Combination for Incremental Grammar Fragment Learning-IFSA/EUFSLAT 2009
  • Minimal Combination for Incremental Grammar Fragment Learning-IFSA/EUFSLAT 2009 Minimal Combination for Incremental Grammar Fragment Learning-IFSA/EUFSLAT 2009
  • Transcript

    • 1. ORDER INDEPENDENT INCREMENTAL EVOLVING FUZZY GRAMMAR FRAGMENT LEARNER
      • Nurfadhlina Mohd Sharef ,
      • Department of Computer Science,
      • Faculty of Computer Science and Information Technology,
      • University Putra Malaysia,
      • Malaysia.
      • [email_address] ,
      • [email_address] ,
      • Trevor Martin,
      • Yun Shen
      • Artificial Intelligence Group,
      • Intelligent System Lab,
      • University of Bristol
      • Bristol, United Kingdom
      • [email_address] ,
      • [email_address]
    • 2. OUTLINE
      • Introduction
      • Text Fragment Learning
      • Fuzzy Grammar Fragment
      • Order Independent
    • 3. ** Source from World Incidents Tracking System Human is able to understand a class without following a strict pattern
    • 4. SUMMARY EXAMPLES
      • “ On 27 May 2004 , in Nadapuram, Kerala, India, a bomb exploded at a store, causing moderate damage to the establishment but no casualties. No group claimed responsibility.”
      • “ On 27 May 2004 , at about 7:30 AM , in the Tanahu District, Nepal, a press vehicle ran over a landmine, killing the driver and injuring two passengers. No group claimed responsibility, although it is widely believed the Communist Party of Nepal (Maoist)/United People's Front was responsible.”
      • “ On 27 May 2004 , at night , in Pulwama, Jammu and Kashmir, India, armed assailants fired upon and killed a former Special Police Officer in his home. No group claimed responsibility.”
      • ** Source from World Incidents Tracking System
      date date date time time victim victim
    • 5. TEXT FRAGMENT LEARNING learn the underlying grammar patterns of similar texts ; exploiting both syntactical and semantic properties Text Fragment Examples XML Tag: Event Type - Bomb exploded - Explosion occurred - detonated a bomb -detonated a timed improvised explosive device Bombing - Attacks to occur - Attackers threw a grenade - Assailants attacked a security vehicle - Gunmen killed a member Armed Attack
    • 6. BOMBING TEXT FRAGMENT
      • “ On 1 January 2004, in Srinagar, Jammu and Kashmir, India, an assailant on a bicycle was carrying a bomb, which prematurely exploded , injuring six civilians. No group claimed responsibility.”
      • “ On 27 May 2004, in Nadapuram, Kerala, India, a bomb exploded at a store, causing moderate damage to the establishment but no casualties. No group claimed responsibility.”
      • “ On 2 February 2004, in Khowst, Nader Shah Kot District, Afghanistan, an explosion occurred at a concert, frightening the crowd, but causing no injuries. No group claimed responsibility.”
      • “ On 1 March 2004, in Burgos, Italy, an attacker detonated a bomb outside the apartment home of the mayor of Burgos, killing the official's father. The mayor had been a target of several attacks and threats, including a recent bombing at his mother's grave. No group claimed responsibility.”
      • ** Source from World Incidents Tracking System
    • 7. Learning Fuzzy Grammar Fragments
      • “ To investigate
      • an incremental evolving fuzzy grammar fragment learning
      • with independent-order feature”
    • 8. FUZZY GRAMMAR FRAGMENT ** Grammar derivation is done using a set of predefined terminal sets of type regular expression , enumeration and compound learn the underlying structure of the data convert the texts into a more structured form + Text Fragment Grammar Fragment
      • Bomb exploded
      • Explosion occurred
      • detonated a bomb
      • a timed improvised explosive device detonated
      • detonated explosives
      • bombers threw grenades
      • BombType-BombAction
      • BombAction
      • BombAction-Article-Bomb Type
      • Article-Bomb Type- BombAction
      • BombAction-Bomb Type
      • CriminalList-anyword- Bomb Type
    • 9. EVOLVING GRAMMAR ISSUES Grammar Class Text Class
      • How to recognize the fragment
      • How to represent the grammar
      • ? How to generalize the grammar
      Text Fragment1 Word 1 -Word 2 -…-Word n Grammar1 Term 1 -Term 2 -…-Term n Text Fragment2 Word 1 -Word 2 -…-Word n Grammar2 Term 1 -Term 2 -…-Term n
      • Automatic Generation
      • How to tell one grammar is better ?
      Grammar1 Term 1 -Term 2 -…-Term n
    • 10. GRAMMAR SIMILARITY Table 1: Example of string edit distance operation (*I:Insert, D:Delete, S:Substitute) Table 2: Example of Grammar Edit Distance Operation (*I:Insert, D:Delete, S:Substitute) Cost(sg ,tg) = <I D S Rs Rt>=<1 1 1 null null> I:Insert D:Delete S:Substitute Rs: remaining in Source Rt: remaining in Target Source string W E D N E S D A Y Target string T U E S D A Y Edit distance* S=1 S=1 D=1 D=1 = = = = = Source grammar, sg Number Word Word Streetending Placename Target grammar, tg Number Placename Streetending Placename Countyname Edit distance* = S=1 D=1 = = I=1
    • 11. GRAMMAR COMBINATION Start s=new string maxMem=membership(s,TG) maxMem<1? costST=costTS=1 Y gx=Combine(sg,tg) costST=1 && costTS=0 gx=sg N Y N costST=0 && costTS=1 gx=tg Y Update TG: GTj={GTj-1-gti} union {gx} gx=sg N sg=deriveGrammar(s) tg=target grammar with maxMem costST=grammarSimilarity(sg,tg) costTS=grammarSimilarity (tg,sg) End Y N
    • 12. MINIMAL COMBINATION RULES Source Grammar Target Grammar Cost (Source, Target) Cost (Target, Source) Combination Operation Combined grammar a-b-c a-b 0 1 0 - - 1 0 0 - - Insert a-b-[c] a-b a-b-c 1 0 0 - - 0 1 0 - - Insert a-b-[c] a-b-c a-B-c 0 0 0 - - 0 0 1 - - Merge a-B-c, B>b a-B-c a-b-c 0 0 1 - - 0 0 0 - - Merge a-B-c, B>b a-F-c a-G-c 0 0 1 - - 0 0 1 - - Create a-X-c , X:=F||G,
    • 13. ORDER INDEPENDENT IEFG
      • Let α be a triplet α =< S, GS,GT> where S is a finite permutation of strings i.e. a sequence in which each string appears exactly once.
      • parse) S.
      • GT is the set of combined grammars that represents (can
      • parse) S.
      • In order to show GS = GT we note that
      • GS ≤ GT ↔ Ext(GS) ⊆ Ext(GT)
      • GT ≤ GS ↔ Ext(GT) ⊆ Ext(GS)
      • where
      • Ext(GS) is the set of strings parse-able by GS
      • Ext(GT) is the set of strings parse-able by GT
      • Hence it suffices to show that
      • Ext(GS) = Ext(GT)
    • 14. THEOREM 1: FOR α =< S,GS,GT> EXT(GS)=EXT(GT)
      • Proof by induction
      • Basis n=1
      • Clearly GS = {gs1} = GT, so Ext(GS) = Ext(GT)
      • Inductive step
      • We assume that Ext(GSj-1) = Ext(GTi-1) for some arbitrary value i=j and j>1 and show that
      • Ext(GSj) = Ext(GTi)
      • Note that
      • Ext(GSj) = Ext(GSj-1)∪ Ext(gsj)
    • 15. Let: Ext(GS j ) = Ext(GS j-1 ) ∪ Ext(gs j ) g x =Combine(gs j ,gt i ) Ext(g x ) = Ext(gs j ) ∪ Ext (gt i ) Case1: Combine( gs j ,gt i ) if Cost(gs j ,gt i )=Cost(gt i , gs j )= 1 In this case, Ext(GT i ) = Ext(GT i-1 - {gt i }) ∪ Ext(g x ) Hence Ext(GT i ) = (Ext(GTi-1) - (Ext(gt i )) ∪ Ext(g x ) = Ext(GT x-1 ) ∪ Ext(gs j ) Case2: Combine( gs j ,gt i ) if gs j is more general than gt i i.e. Ext(gt i ) ⊆ Ext(gs j ) In this case, Ext(GT i ) = Ext(GT i-1 ) ∪ Ext(gs j ) Case3: Combine( gs j ,gt i ) if gt i is more general than gs j i.e. Ext(gs j ) ⊆ Ext (gt i ) In this case, Ext(GT i ) = Ext(GT i-1 ) Therefore Ext(GS j-1 ) = Ext(Gt j-1 ) implies Ext(GS j ) = Ext(Gt i ) Thus in all cases the inductive hypothesis is true and Ext(GSj)=Ext(Gti) ■
    • 16. LEMMA 2.1
      • For any two permutations S and S*, giving derived grammars GS and GS*
      • Ext(GSj) = Ext(GSj*)
      • Proof
      • Each example string sj leads to a derived grammar gsi. Clearly from the definition
      • Ext(GS) = Ext(gs1) ∪ Ext(gs2) ∪ …
      • This is independent of the order in which the example strings are presented.
    • 17.
      • Theorem 2 : Given α =< S, GS ,GT> and α * =< S*, GS* ,GT*>,
      • Then Ext(GTi) = Ext(GTi*)
      • Proof
      • By lemma 2.1, Ext(GSj) = Ext(GSj*)
      • By theorem 1, Ext(GSj) = Ext(Gti) and Ext(GSj*) = Ext(GTi*)
      • Hence Ext(GTi) = Ext(GTi*)
      • Corollary 2
      • Cost( GT,GT*) = Cost(GT*,GT)= <0 0 0 null null>
      • This ends the proof of Theorem 2■
      To show that the IEFG process is independent of the order in which examples are presented, we consider a different permutation S* leading to  * =<S*, GS* ,GT*> and show that Ext(GTi) = Ext(GTi*)
    • 18. EXAMPLE
      • generated results may not be syntactically identical but rather yield same (approximate) parsing coverage even when the pattern instances are presented in different orders.
    • 19. CONCLUSION
      • An algorithm that features independent training order can ensure robust results.
      • This paper discusses an order-independent fuzzy grammar fragment learning method which is implemented using incremental evolving method.
      • The formalized theory is supported with empirical evidence which generates grammars that have equal (approximated) parsing coverage of the trained dataset regardless of the orders .

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