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©2007 Rommel Novaes Carvalho –University of Brasília
A G U I T o o l fo r P la u s ib le R e a s o n in gA G U I T o o l f...
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A GUI Tool for Plausible Reasoning in the Semantic Web Using MEBN

Presentation given by Rommel N. Carvalho at the ISDA conference in 2007. The paper related to this presentation was later invited to be extended to a book chapter.

Book chapter: http://link.springer.com/chapter/10.1007/978-3-540-88045-5_2

Abstract
As the work with semantics and services grows more ambitious in the Semantic Web community, there is an increasing appreciation on the need for principled approaches for representing and reasoning under uncertainty. Reacting to this trend, the World Wide Web Consortium (W3C) has recently created the Uncertainty Reasoning for the World Wide Web Incubator Group (URW3-XG) to better define the challenge of reasoning with and representing uncertain information available through the World Wide Web and related WWW technologies. In according to the URW3-XG effort this Chapter presents the implementation of a graphical user interface (GUI) for building probabilistic ontologies, an application programming interface (API) for saving and loading these ontologies and a grammar proposal to specify formulas for creating conditional probabilistic tables dynamically. The language used for building probabilistic ontologies is Probabilistic OWL (PR-OWL), an extension for OWL based on Multi-Entity Bayesian Network (MEBN). The GUI, API, and the compiler for the proposed grammar were implemented into UnBBayes-MEBN, an open source, Java-based application that provides an easy way for building probabilistic ontologies and reasoning based on the PR-OWL/MEBN framework.

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A GUI Tool for Plausible Reasoning in the Semantic Web Using MEBN

  1. 1. ©2007 Rommel Novaes Carvalho –University of Brasília A G U I T o o l fo r P la u s ib le R e a s o n in gA G U I T o o l fo r P la u s ib le R e a s o n in g in th e S e m a n tic W e b u s in g M E B Nin th e S e m a n tic W e b u s in g M E B N S ession B-III: Intelligent Data Mining Rommel Novaes Carvalho rommel.carvalho@ gmail.com A d v is o r: P ro f. D r. M a rc e lo L a d e ira C o -A d v is o r: D r. P a u lo C e s a r G . d a C o s ta Intelligent S ystems Design and Applications (IS DA), UERJ – Rio de Janeiro, Brazil 23/10/2007
  2. 2. ©2007 Rommel Novaes Carvalho – University of Brasília 2 Te a m M s S tu d e n t R o m m e l N o v a e s C a rv a lh o /U n B - B ra z il A d v is o r P ro f. D r. M a rc e lo L a d e ira /U n B - B ra z il C o -A d v is o r D r. P a u lo C é s a r G . d a C o s ta /G M U - U S A C o m p u te r S c ie n c e S tu d e n ts L a é c io L . d o s S a n to s /U n B - B ra z il S h o u M a ts u m o to /U n B - B ra z il
  3. 3. ©2007 Rommel Novaes Carvalho – University of Brasília 3 A g e n d a In tro d u c tio n U n d e rs ta n d in g B N lim ita tio n s U n d e rs ta n d in g M E B N B N + F O L = M E B N M T h e o ry a n d M F ra g M E B N + O W L = P R -O W L B u ild in g m y firs t M T h e o ry S S B N in U n B B a y e s K B - E n titie s K B - F in d in g s Q u e ry B o o to m -u p a lg o rith m C o n c lu s io n s
  4. 4. ©2007 Rommel Novaes Carvalho – University of Brasília 4 In tro d u c tio n R e p re s e n tin g a n d c o m m u n ic a tin gR e p re s e n tin g a n d c o m m u n ic a tin g N e e d o f re p re s e n tin g a n d c o m m u n ic a tin g In fo rm a tio n te c h n o lo g y re v o lu tio n -> k n o w le d g e re v o lu tio n D a ta d riv e n a c tiv itie s -> k n o w le d g e d riv e n a c tiv itie s T h e S e m a n tic W e b (S W )w ill a c h ie v e its fu ll p o te n tia l w h e n it b e c o m e s a p la c e w h e re d a ta c a n b e s h a re d a n d p ro c e s s e d b y a u to m a tic to o ls th e s a m e w a y it is c u rre n tly d o n e b y h u m a n b e in g s [2]. O n to lo g ie s c o n ta in a c o m m o n s e t o f te rm s fo r d e s c rib in g a n d re p re s e n tin g a d o m a in a llo w in g th e S W a c h ie v e its fu ll p o te n tia l. “W h ite ” - s y n ta c tic <> S W <> u n c e rta in ty S W U R W 3-X G
  5. 5. ©2007 Rommel Novaes Carvalho – University of Brasília 5 In tro d u c tio n U n c e rta in ty in S e m a n tic W e bU n c e rta in ty in S e m a n tic W e b O n e o f th e m o s t p ro m is in g a p p ro a c h e s to d e a l w ith u n c e rta in ty in th e S W is B a y e s ia n n e tw o rk s (B N )[6] H o w e v e r, B N s h a v e s o m e lim ita tio n s o n re p re s e n ta tio n a l p o w e r th a t re s tric ts th e ir u s e fo r th e S W N u m b e r o f v a ria b le s is fix e d N o re c u rs io n U s e o f th e e x p re s s iv e n e s s o f firs t o rd e r lo g ic (F O L )to o v e rc o m e th is s h o rtc o m in g s T h is fra m e w o rk is b a s e d o n th e p ro b a b ilis tic o n to lo g y la n g u a g e P R -O W L [7, 8], w h ic h u s e s M u lti-E n tity B a y e s ia n N e tw o rk s (M E B N )[9, 1 0] a s its u n d e rly in g lo g ic .
  6. 6. ©2007 Rommel Novaes Carvalho – University of Brasília 6 U n d e rs ta n d in g B N lim ita tio n s N u m b e r o f v a ria b le sN u m b e r o f v a ria b le s P ro b le m : D is c rim in a te s ta rs h ip s a n d m a k eP ro b le m : D is c rim in a te s ta rs h ip s a n d m a k e d e c is io n s b a s e d o n u n c e rta in a n d in c o m p le ted e c is io n s b a s e d o n u n c e rta in a n d in c o m p le te in fo rm a tio n .in fo rm a tio n .
  7. 7. ©2007 Rommel Novaes Carvalho – University of Brasília 7 U n d e rs ta n d in g B N lim ita tio n s N u m b e r o f v a ria b le sN u m b e r o f v a ria b le s P ro b le m : D is c rim in a te s ta rs h ip s a n d m a k eP ro b le m : D is c rim in a te s ta rs h ip s a n d m a k e d e c is io n s b a s e d o n u n c e rta in a n d in c o m p le ted e c is io n s b a s e d o n u n c e rta in a n d in c o m p le te in fo rm a tio n .in fo rm a tio n . Bayesian ReasoningBayesian Reasoning:: Update old beliefs with newUpdate old beliefs with new evidences. All new data areevidences. All new data are considered.considered.
  8. 8. ©2007 Rommel Novaes Carvalho – University of Brasília 8 U n d e rs ta n d in g B N lim ita tio n s N u m b e r o f v a ria b le sN u m b e r o f v a ria b le s P ro b le m : D is c rim in a te s ta rs h ip s a n d m a k eP ro b le m : D is c rim in a te s ta rs h ip s a n d m a k e d e c is io n s b a s e d o n u n c e rta in a n d in c o m p le ted e c is io n s b a s e d o n u n c e rta in a n d in c o m p le te in fo rm a tio n .in fo rm a tio n .
  9. 9. ©2007 Rommel Novaes Carvalho – University of Brasília 9 U n d e rs ta n d in g B N lim ita tio n s N u m b e r o f v a ria b le sN u m b e r o f v a ria b le s W h a t h a p p e n s if m o re th a n o n e s ta rs h ip s h o wW h a t h a p p e n s if m o re th a n o n e s ta rs h ip s h o w u p a t th e s a m e tim e ? B u ild a B N fo r e a c hu p a t th e s a m e tim e ? B u ild a B N fo r e a c h p o s s ib le c o n te x t?p o s s ib le c o n te x t?
  10. 10. ©2007 Rommel Novaes Carvalho – University of Brasília 10 U n d e rs ta n d in g B N lim ita tio n s N u m b e r o f v a ria b le sN u m b e r o f v a ria b le s W h a t h a p p e n s if m o re th a n o n e s ta rs h ip s h o wW h a t h a p p e n s if m o re th a n o n e s ta rs h ip s h o w u p a t th e s a m e tim e ? B u ild a B N fo r e a c hu p a t th e s a m e tim e ? B u ild a B N fo r e a c h p o s s ib le c o n te x t?p o s s ib le c o n te x t?
  11. 11. ©2007 Rommel Novaes Carvalho – University of Brasília 11 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  12. 12. ©2007 Rommel Novaes Carvalho – University of Brasília 12 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  13. 13. ©2007 Rommel Novaes Carvalho – University of Brasília 13 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  14. 14. ©2007 Rommel Novaes Carvalho – University of Brasília 14 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  15. 15. ©2007 Rommel Novaes Carvalho – University of Brasília 15 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  16. 16. ©2007 Rommel Novaes Carvalho – University of Brasília 16 U n d e rs ta n d in g B N lim ita tio n s R e c u rs io nR e c u rs io n L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip .L e ts s u p p o s e th a t th e re is ju s t o n e s ta rs h ip . H o w to re a liz e if th e D M R is d u e to th e z o n eH o w to re a liz e if th e D M R is d u e to th e z o n e n a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a kn a tu re (a le a to ry )o r to th e s ta rs h ip 's c lo a k m o d e (c o n s ta n t)?m o d e (c o n s ta n t)?
  17. 17. ©2007 Rommel Novaes Carvalho – University of Brasília 17 U n d e rs ta n d in g M E B N B N + F O L = M E B NB N + F O L = M E B N M E B N is a fo rm a lis m th a t b rin g s to g e th e r th e e x p re s s iv e n e s s o f firs t o rd e r lo g ic (F O L )w ith B N ’s a b ility to p e rfo rm p la u s ib le re a s o n in g .
  18. 18. ©2007 Rommel Novaes Carvalho – University of Brasília 18 U n d e rs ta n d in g M E B N M T h e o ry a n d M F ra gM T h e o ry a n d M F ra g Context Nodes Input Nodes Resident Nodes A n M T h e o ry is a s e t o f M F ra g s th a t s a tis fy c e rta in F O L c o n s is te n c e c o n d itio n s th a t g u a ra n ty th e e x is te n c e o f a u n iq u e J P D (J o in t P ro b a b ility D is trib u tio n )u n d e r its R V s (R a n d o m Va ria b le s ). M F ra g c o n s is ts o f b o th a s e t o f C P Ts a n d F O L lo g ic a l c o n s tra in ts th a t fix e d th e ir v a lid a tin g c o n d itio n s .
  19. 19. ©2007 Rommel Novaes Carvalho – University of Brasília 19 U n d e rs ta n d in g M E B N M E B N + O W L = P R -O W LM E B N + O W L = P R -O W L P R -O W L w a s p ro p o s e d a s a n e x te n s io n to th e O W L la n g u a g e b a s e d o n M E B N , w h ic h c a n e x p re s s a p ro b a b ilis tic d is trib u tio n u n d e r a n y a x io m a tic F O L th e o ry m o d e l.
  20. 20. ©2007 Rommel Novaes Carvalho – University of Brasília 20 B u ild in g m y firs t M T h e o ry R e s id e n t n o d e sR e s id e n t n o d e s
  21. 21. ©2007 Rommel Novaes Carvalho – University of Brasília 21 B u ild in g m y firs t M T h e o ry In p u t n o d e s a n d re c u rs io nIn p u t n o d e s a n d re c u rs io n
  22. 22. ©2007 Rommel Novaes Carvalho – University of Brasília 22 B u ild in g m y firs t M T h e o ry C o n te x t n o d e sC o n te x t n o d e s
  23. 23. ©2007 Rommel Novaes Carvalho – University of Brasília 23 B u ild in g m y firs t M T h e o ry D in a m ic ta b le a n d n u m b e r o f v a ria b le sD in a m ic ta b le a n d n u m b e r o f v a ria b le s
  24. 24. ©2007 Rommel Novaes Carvalho – University of Brasília 24 B u ild in g m y firs t M T h e o ry S a v in g th e u b f a n d p r-o w l fileS a v in g th e u b f a n d p r-o w l file UBF PR-OWL UnBBayes Save
  25. 25. ©2007 Rommel Novaes Carvalho – University of Brasília 25 S S B N in U n B B a y e s K B - E n titie sK B - E n titie s
  26. 26. ©2007 Rommel Novaes Carvalho – University of Brasília 26 S S B N in U n B B a y e s K B - F in d in g sK B - F in d in g s
  27. 27. ©2007 Rommel Novaes Carvalho – University of Brasília 27 S S B N in U n B B a y e s Q u e ryQ u e ry HarmPotential(!ST4, !T0) = ?HarmPotential(!ST4, !T0) = ?
  28. 28. ©2007 Rommel Novaes Carvalho – University of Brasília 28 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  29. 29. ©2007 Rommel Novaes Carvalho – University of Brasília 29 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  30. 30. ©2007 Rommel Novaes Carvalho – University of Brasília 30 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  31. 31. ©2007 Rommel Novaes Carvalho – University of Brasília 31 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  32. 32. ©2007 Rommel Novaes Carvalho – University of Brasília 32 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  33. 33. ©2007 Rommel Novaes Carvalho – University of Brasília 33 S S B N in U n B B a y e s B o tto m -u p a lg o rith mB o tto m -u p a lg o rith m
  34. 34. ©2007 Rommel Novaes Carvalho – University of Brasília 34 C o n c lu s io n s A G U I w a s d e v e lo p e d to fa c ilita te th e c re a tio n o f p ro b a b ilis tic o n to lo g ie s b u ilt o n b o th M F ra g s a n d M th e o rie s . A M E B N C P T fo rm u la e d ito r w a s d e v e lo p e d to d e a l w ith p re v io u s ly u n k n o w n n u m b e r o f n o d e s . F a c ilitie s w e re p ro v id e d to c re a te , lo a d , a n d s a v e M E B N m o d e ls in th e P R -O W L file fo rm a t. P o s s ib ly, th e firs t M E B N fra m e w o rk im p le m e n ta tio n in th e w o rld . It m a k e s e a s ie r th e ta s k o f m o d e llin g re a l d o m a in b a s e d o n M E B N a n d P R -O W L . G o o d fo r re s e a rc h a s U n B B a y e s is a n o p e n s o u rc e s o ftw a re . T h is re s e a rc h re p re s e n ts a c o n trib u tio n to th e S W
  35. 35. ©2007 Rommel Novaes Carvalho – University of Brasília 35 Q & A – th a n k y o u !
  36. 36. ©2007 Rommel Novaes Carvalho – University of Brasília 36 U n B B a y e s C u rre n t S ta te A lp h a v e rs io n s c h e d u le d to J a n u a ry 2008, in c lu d in g : S S B N a lg o rith m a c o m p le te to y c a s e s tu d y S ta rtre k A re a l c a s e s tu d y s c h e d u le d to J u ly 2008 C o m p le te u s e r g u id e in J u ly 2008 C o n ta c t: ro m m e l.c a rv a lh o @ g m a il.c o m p c o s ta @ g m u .e d u

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