A Knowledge-Based information Extraction Prototype for Data-Rich Documents in the Information...

7/31/2019 A Knowledge-Based information Extraction Prototype for Data-Rich Documents in the Information Technology Domain

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m

m


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cardA(.)

W


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cardA()

P


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,


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O = {S,C,h,g}

S

Cp

Ct

h h : (Cp S) (Cp Ct)

h hg

g : Cp (Cp Ct)g g

O OL = {S,C,h,g,L,f}

L

f f : (c1, c2, . . . , cn) L n 1ci C c1, c2, . . . , cn h

g Lf

h g f

OO

S C h g


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Brand

MHz

MBKB

DecimalReal Integer

GHz

GB

Laptop

Processor

ProductID

Family

FrequencyMagnitude

Model

Speed

FrequencyMeasurement

FrequencyUnits

Cache

SizeLevel

FSBInstalled Max.Installable

Memory

MemorySize

MemoryMagnitude

Magnitude

MemoryUnits

HardDisk ...

...

......

...

...

...

...

has-parthas-attribute

(is-a)-1

Initialnode

Internalnode

Terminalnode


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118104

56

26

14 145 7 6 1 1 1 1 1

0

40

80

120

0 1 2 3 4 5 6 7 8 9 10 11 12 23

node out-degree

countingofnodes

(Lap

top

)

(Tim

eU

nit

s)

(Distance

Un

its

)

(Ba

ttery

)

(Hard

Disk)

( )terminalnodes

100

1510

6 4 2 1 3 1 1 1 1 1 1 1

1 2 3 4 5 6 7 8 9 12 13 15 17 18 45

node in-degree

countingofnodes

(Boo

lean

)

(Bran

d)

(Integer)

(Fam

ily

)

(Magn

itu

de)

(Tec

hno

logy

)

(Version

)

(Mo

de

l,Digit)

(TimeMeasurement)

350307


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REF_HardDisk

[HardDisk,HD,HDD,HardDiskDrive,Disk,HardDrive]

CONCEPT

TERMS

TOKENS


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smsn m n O(mn)

O(min(m, n))


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S U N D A Y

0 1 2 3 4 5 6

S 1 0 1 2 3 4 5

A 2 1 1 2 3 3 4

T 3 2 2 2 3 4 4

U 4 3 2 3 3 4 5

R 5 4 3 3 4 4 5

D 6 5 4 4 3 4 5

A 7 6 5 5 4 3 4

Y 8 7 6 6 5 4 3

k

G

d(c1, c2)

a b

c || ||a ca,

c,a ca,b


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sm sn m n

dbag(sm, sn) = max{|sm sn|, |sn sm|}

a,a,a,b a,a,b,c,c a

O(mn)O(m + n)

x, y

N CD(x, y) =C(xy) min {C(x), C(y)}

max {C(x), C(y)}C(x) x C(xy)

x y C

C(xx) = C(x) C() = 0

C(xy) C(x)C(xy) = C(yx)

C(xy) + C(z) C(xz) + C(yz)

C


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|AB||AB| R9

max(|A\B|c,|B\A|c)n

2|AB||A|+|B| R10

min(|A\B,|B\A|)max(|A\B|,|B\A|)

|AB||A||B|

S17|AB|

max(|A\B|c,|B\A|c)

2|AB||AB|+|AB| R12

min(|A\B,|cB\A|c)max(|A\B|c,|B\A|c)

|AB|min(|A|,|B|)max(|A|,|B|) R13

min(|A\B,|B\A|)|AB|

|AB|min(|A|,|B|) R14

min(|A|,|B|)|AB|

|A B| R15 min(|A\B|c,|B\A|c)

n|AB|C

nRc3

|AB|c

min(|A|c,|B|c)|AB|

nRc5

|AB|c

|AB|c

R1 |AB|max(|A|,|B|) Rc8 max(|A|c

,|B|c

)|AB|c

R2|AB|c

max(|A\B|c,|B\A|c) Rc14

min(|A|c,|B|c)|AB|c

R4|AB|c

min(|A\B|c,|B\A|c) Sc17

|AB|c

max(|A\B|c,|B\A|c)

R7max(|A\B|,|B\A|)

|AB| Sc18

|AB|c

n

R8max(|A|,|B|)

|AB|

a bsim

simMongeElkan(a, b) =1

|a||a|i=1

max|b|j=1sim(ai, bj)

O(|a| |b|)

O(min(|a|, |b|)3)


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m

simMongeElkanm(a, b) =

1

|a||a|i=1

max

|b|j=1sim(ai, bj)

m1

m

Jaccard(A, B) =|A B||A B|

|.||A B| = |A| + |B| |A B|

Jaccard(A, B) =|A| + |B| |A B|

|A B|

23 = 0.6666

05 = 0

A B m nA a1, a2,...,an b1, b2,...,bm B

card(.)

Jaccard(A, B) =card(A) + card(B) card(A B)

card(A

B)

card(.)

card(a1, a2,...,an) = 1, if (a1 = a2 = ... = an)


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rel1 rel2

1 editDistance(A,B)

max(|A|,|B|)

#commonBigrams(A,B)max(|A|,|B|)

sim(a, b)

sim(a, b)

m = 0.00001

m = 0.5

m = 1.5

m = 2


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card(AB)card(AB)

2card(AB)card(A)+card(B)

card(AB)card(A)card(B)2card(AB)

card(AB)+card(AB)card(AB)min(card(A),card(B))

max(card(A),card(B))card(AB)

min(card(A),card(B))card(AB)

max(card(A),card(B))max(card(A),card(B))

card(AB)

min(card(A),card(B))card(AB)

m = 5

m = 10

m simmax(a, b) = max|a|i=1 max|b|j=1 sim(ai, bj)

sim(a, b)

cardA(.)

cardA(.)

cardA(.)


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0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

similarity threshold

recall precision F-measure

r

r

1 1


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0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

recall

precision

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

recall

precision


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m1 m2 m1 m2

H0

m1 m2

m1 m2

n

W


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n

WW

n

Wn

W n = 12

W


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WilcoxonsRate =test

75

sim(a, b)

WW n = 12


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sim(a, b) W

sim(a, b) W

m

m = 1m

m

W nW


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= 0.75


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IC(c)c

SI MLeacock&Chodorow(a, b) = log

pathLength(a, b)

2D

depth(x)x

SI MWu&Palmer(a, b) = 2 depth(lcs(a, b))pathLength(a, b) + 2 depth(lcs(a, b))


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Brand

MHzDecimalReal GHz

Laptop

Processor

ProductID

Family

FrequencyMagnitude

Model

Speed

Frequency

FrequencyUnits

Cache FSB BusWidth

Memory HardDisk...

...

...

...

...

SI MpathLenght(a, b) = depth(a) + depth(b) 2 lcs(a, b)

LenFactor(a, b) =pathLength(a, b)

2 D

Spec(x) =depth(x)

clusterDepth(x)

SpecFactor(a, b) = |Spec(a) Spec(b)|

SI MAltinas(a, b) =1

1 + LenFactor(a, b) + SpecFactor(a, b)

clusterDepth(x)


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Brand

MHzDecimalReal GHz

Laptop

Processor

ProductID

Family

FrequencyMagnitude

Model

Speed

Frequency

FrequencyUnits

Ca ch e FS B BusWidth

Memory HardDisk...

...

...

...

...

...

w=1

w=2

w=3

w=4w=4

w=3

WeightedPathLength (Brand,GHz)=3+4+4+3+2+1=17


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w1 w2 w3 w4 w5

senses

words

t3 t5t5


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Term

senses

tokens

t1 t2 t3 t4 t5


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distance = 1 normalizedSimilarity


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Integer

Laptop

HardDisk

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

HardDisk

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

HardDisk

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

HardDisk

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

HardDisk

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

VideoAdapter

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

VideoAdapter

MemorySize

MemoryMagnitude

Installed

Integer

Laptop

Memory

MemorySize

MemoryMagnitude

MaxInstallable

Integer

Laptop

Memory

MemorySize

MemoryMagnitude

Installed

Laptop

Processor

CacheSize

MemorySize

MemoryMagnitude

Cache

Integer

Megabyte

Laptop

VideoAdapter

MemorySize

MemoryUnits

MaxInstallable

Megabyte

Laptop

VideoAdapter

MemorySize

MemoryUnits

Installed

Megabyte

Laptop

Memory

MemorySize

MemoryUnits

MaxInstallable

Megabyte

Laptop

Memory

MemorySize

MemoryUnits

Installed

Laptop

Processor

CacheSize

MemorySize

MemoryUnits

Cache

Megabyte

MB512... ...

Laptop

Processor

Cache

REF_Cache

Cache


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MB Cache512...

...

..

.

...

...

Semantic

Path#1

Semantic

Path #5

Semantic

Path #5

Semantic

Path #6

Semantic

Path #n

Semantic

Path#4

Semantic

Path#4

Semantic

Path #2

Semantic

Path #2

Semantic

Path #3

Semantic

Path #3

Semantic

Path #1

Semantic

Path #1

w

Semantic

RelatednessMetric

P


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P


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Atoken#1

Atoken#1

Btoken#2

Btoken#2

token#3

Ctoken#4

Dtoken#5

token#5

Etoken#6

token#6

token#7

token#7

token#8

token#8

Xtoken#3

Ytoken#4

truepositives

falsepositives

falsenegatives

truenegatives

targe

t

se

lec

ted

(B)(A)

[0, 1]

precision = T PT P + F P

recall =T P

T P + F N

F measure = 2 precision recallprecision + recall


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0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

threshold

Recall

Precision

F-measure

Recall-Baseline

Precision-Baseline

F-measure-Baseline

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Recall

Precision


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0

0.2

0.4

0.6

0.8

1

0 25 50 75 100

noisy lexicon level

F1-score

ExactMatch-SimpleStr ExactMatch-MongeElkan

EditDistance-SimpleStr EditDistance-MongeElkan

0

0.2

0.4

0.6

0.8

1

0 25 50 75 100

noisy lexicon level

F1-score

ExactMatch-SimpleStr ExactMatch-MongeElkan

EditDistance-SimpleStr EditDistance-MongeElkan


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0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

0

0.3

0.6

0.9

0.5 0.6 0.7 0.8 0.9 1

EditDistance-MongeElkan

2grams(Dice)-MongeElkan0

EditDistance-cosine(A)

no

ise

free

lex

icon

no

isy

le

xicon

25

no

isy

lex

icon

50

no

isy

lex

icon

75

no

isy

lex

icon

100

F-measure


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0

50,000

100,000

150,000

200,000

250,000

0 0.2 0.4 0.6 0.8 1

threshold

#ofgraphnodes


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Score =# of wordsin the match

# of characters in theacronym

Score


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bitsacronymmodelbitstextcompressionmodel

= 0.2


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S

Pattern

Document

... .... . . .

Serial

5400 rpm

T

T

A-

A A

A

GB120:DiskHard


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0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1threshold

F-Measure

Baseline (ExactMatch-SimpleStr.)

Best Configuration

Best Conf. + Acronym Matcher


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hasparthaspart

haspart

hasparthasparthaspart

haspart

hasparthaspart

hasparthaspart

hasparthaspart

haspart

hasparthaspart

haspart

hasparthaspart


haspart


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haspart

hasparthaspart

hasparthaspart

haspart

hasparthaspart

haspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

haspart

hasparthaspart

hasparthasparthasparthaspart

hasparthaspart

hasparthaspart


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haspart

hasparthaspart

haspart

hasparthaspart

haspart


hasparthaspart

hasparthaspart

haspart

hasparthaspart

hasparthaspart

hasparthaspart

haspart


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haspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

hasparthaspart

haspart

hasparthaspart

hasparthaspart

hasparthaspart

haspart


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haspart

hasparthaspart

haspart

hasparthaspart

haspart


hasparthaspart

hasparthaspart

hasparthaspart

isaisa

isahaspart

isaisa

isa

isa


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isa

isaisa

isaisa

isaisa

isa

hasparthaspart

isa


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A Knowledge-Based information Extraction Prototype for Data-Rich Documents in the Information...

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Transcript of A Knowledge-Based information Extraction Prototype for Data-Rich Documents in the Information...