Minimal Combination for Incremental Evolving Fuzzy

Grammar Fragment LearningNurfadhlina Mohd Sharef, Trevor Martin, Yun Shen

Artificial Intelligence Group, University of Bristol, BS8 1TR UKennms@bris.ac.uk, trevor.martin@bris.ac.uk, yun.shen@hotmail.co.uk

Outline

• Background of problem

• Literature review

• Fuzzy text pattern learning

• Grammar Combination

• Independent Order Grammar Learning

• Conclusion

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Text Fragments Structure

• Text Fragment Patterns• Similar but not identical• Less Structured• Text segments and simple sentences

• Application: Instance matching, Dialogue system, Question Answering, etc

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Existing Approaches

• full language model

• tagging-based information extraction

• document distributions and statistical model

• evolutionary genetic algorithms

• Schema/structure matching

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Grammars for Postal Addressnumber, street name, town, postCode‘21 London Rd Ipswich Suffolk IP1 2EZ’

• And others:• ‘29 Meredith Rd Ipswich’

number, street name,town• ‘Belfairs Hotel 33 Graham Rd Ipswich’

word, business, number, street name, town• mamma's pizza 46 st.matthews st ipswich • beautiful designs 8 norwich rd ipswich

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Learning Fuzzy Grammar Fragments

“To investigate

an incremental evolving fuzzy grammar fragment learning

with independent-order feature”

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

ISSUES

• Grammar Variety-incremental evolving

• Grammar Derivation-fuzzy grammar, fuzzy membership

• Grammar Similarity- fuzzy grammar similarity

• Grammar combination-maximal, minimal, flexible, compact

• Flexible-independent order

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Fuzzy Approach for Text Pattern Learning

• Fuzzy Membership• relation between

text and the grammar

fragment

• Fuzzy Grammar

Similarity• Distance

between grammars• <I D S Rs Rt>

ALPHANUMERIC

NUMBER ALPHABETIC

ANYWORD

PC1 PC2

PLACENAME BUSINESS TYPE

ETC

CITY NAME

Figure 5: Partial Order Table for UK Address

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Grammar SimilaritySource 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 = = = = =

Table 1: Example of string edit distance operation (*I:Insert, D:Delete, S:Substitute)

Source grammar

Number Word Word Streetending Placename

Target grammar

Number Placename Streetending Placename Countyname

Edit distance*

= S=1 D=1 = = I=1

Table 2: Example of Grammar Edit Distance Operation (*I:Insert, D:Delete, S:Substitute)

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Start s=new string maxMem=membership(s,TG)

maxMem<1?

Grammar Learning

costST=costTS=1Y

gx=Combine(sg,tg)

costST=1 && costTS=0 gx=sgN

Y

N

costST=0 && costTS=1 gx=tgY

Update TG:GTj={GTj-1-gti} union {gx}

gx=sgN

sg=deriveGrammar(s)tg=target grammar with maxMem

costST=grammarSimilarity(sg,tg)costTS=grammarSimilarity (tg,sg)

End

Y

N

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Minimal Combination Algorithm

Source Grammar

Target Grammar

Cost(Source,Target)

Cost(Target,Source)

Combination Operation

Combinedgrammar

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,GF

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Experiment-Parsing Coverage• Data

• Restaurant.xml

and yellowpages.xml

• Setting• 25% train, 75% test

• Parameters• # max parsing of

each string• # max parsing by

each grammar

Setting

DatasetAverage

Maximum Parsing (%)

FG Restaurant 89.5

IEG Restaurant 100

FG Yellowpages 97

IEG Yellowpages 100

FG: Fuzzy Grammar

IEG: Incremental Evolving Fuzzy Grammar

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09

Experiment-Independent Order Grammar Learning

• To compare parsing coverage

of grammars generated from different orders

G1: a a b cG2: b a cG3: a c G4: a a cG5: a a a

Order 1:

G1-G2-G3-G4-G5

Order 2:

G4-G5-G2-G1-G3

Order 3:

G2-G4-G1-G3-G5

a a [b] c (1+4) a a a (4+5) (b||a) a c (2+4)

[b] a c (2+3) [b] a c (2+3) a a b c (1)

a a a (5) a a b c (1) a c (3)

a a a (5)

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Fuzzy Grammar Fragment Learning, IFSA 09

Conclusion and Future Work

• Incremental evolving fuzzy grammar fragment learning with independent-order effect

• Latest Achievements• Formal proving of independent order in minimal

combination• Flexible Combination and formal proving• Preliminary Theme Classification

• More Future Works• Focus on softer structures for grammar learning and

theme classification

Minimal Combination for Incremental Evolving

Fuzzy Grammar Fragment Learning, IFSA 09