Online Learning of Weighted Relational Rules for Complex Event - PowerPoint PPT Presentation

Online Learning of Weighted Relational Rules for Complex Event Recognition Nikos Katzouris 1 ,Evangelos Michelioudakis 3,1 , Alexander Artikis 2,1 and Georios Paliouras 1 http://cer.iit.demokritos.gr 1 National Center for Scientific Research Demokritos, Athens, Greece 2 University of piraeus, Piraeus, Greece, 3 National University of Athens, Athens, Greece ECML-PKDD 2018 1/19

The problem Setting Event Calculus as a Reasoning Engine holdsAt ( F , T + 1 ) ← initiatedAt F , T ) holdsAtAt ( F , T + 1 ) ← holdsAt ( F , T ) , not terminatedAt ( F , T ) . Very efficient inference: Artikis et al. An Event Calculus for Event Recognition, TKDE, 2015. Input ◮ Recognition ◮ Output � . . . . . . . . . . . . Event Simple Events Recognition Complex Events System . . . . . . . . . . . . Complex Event happensAt ( active ( id 0 ) , 10 ) holdsAt ( coord ( id 0 , 20 . 88 , 11 . 90 ) , 10 ) Definitions happensAt ( active ( id 1 ) , 10 ) holdsAt ( coord ( id 1 , 22 . 34 , 15 . 23 ) , 10 ) holdsAt ( meet ( id 0 , id 1 ) , 11 ) holdsAt ( meet ( id 0 , id 1 ) , 12 ) . . . holdsAt ( meet ( id 0 , id 1 ) , 13 ) initiatedAt ( meet ( X , Y ) , T ) ← . . . happensAt ( active ( X ) , T ) , happensAt ( active ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . Learn this terminatedAt ( meet ( X , Y ) , T ) ← happensAt ( walking ( X ) , T ) , not holdsAt ( close ( X , Y , 25 ) , T ) . From These 2/19

The problem Setting Event Calculus as a Reasoning Engine holdsAt ( F , T + 1 ) ← initiatedAt F , T ) holdsAtAt ( F , T + 1 ) ← holdsAt ( F , T ) , not terminatedAt ( F , T ) . Very efficient inference: Artikis et al. An Event Calculus for Event Recognition, TKDE, 2015. Input ◮ Recognition ◮ Output � . . . . . . . . . . . . Event Simple Events Recognition Complex Events System . . . . . . . . . . . . Complex Event happensAt ( active ( id 0 ) , 10 ) holdsAt ( coord ( id 0 , 20 . 88 , 11 . 90 ) , 10 ) Definitions happensAt ( active ( id 1 ) , 10 ) holdsAt ( coord ( id 1 , 22 . 34 , 15 . 23 ) , 10 ) holdsAt ( meet ( id 0 , id 1 ) , 11 ) holdsAt ( meet ( id 0 , id 1 ) , 12 ) . . . holdsAt ( meet ( id 0 , id 1 ) , 13 ) initiatedAt ( meet ( X , Y ) , T ) ← . . . happensAt ( active ( X ) , T ) , happensAt ( active ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . Learn this terminatedAt ( meet ( X , Y ) , T ) ← happensAt ( walking ( X ) , T ) , not holdsAt ( close ( X , Y , 25 ) , T ) . From These 3/19

The problem Setting Event Calculus as a Reasoning Engine holdsAt ( F , T + 1 ) ← initiatedAt F , T ) holdsAtAt ( F , T + 1 ) ← holdsAt ( F , T ) , not terminatedAt ( F , T ) . Very efficient inference: Artikis et al. An Event Calculus for Event Recognition, TKDE, 2015. Input ◮ Recognition ◮ Output � . . . . . . . . . . . . Event Simple Events Recognition Complex Events System . . . . . . . . . . . . Complex Event happensAt ( active ( id 0 ) , 10 ) holdsAt ( coord ( id 0 , 20 . 88 , 11 . 90 ) , 10 ) Definitions happensAt ( active ( id 1 ) , 10 ) holdsAt ( coord ( id 1 , 22 . 34 , 15 . 23 ) , 10 ) holdsAt ( meet ( id 0 , id 1 ) , 11 ) holdsAt ( meet ( id 0 , id 1 ) , 12 ) . . . holdsAt ( meet ( id 0 , id 1 ) , 13 ) initiatedAt ( meet ( X , Y ) , T ) ← . . . happensAt ( active ( X ) , T ) , happensAt ( active ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . Learn this terminatedAt ( meet ( X , Y ) , T ) ← happensAt ( walking ( X ) , T ) , not holdsAt ( close ( X , Y , 25 ) , T ) . From These 4/19

The problem Setting Event Calculus as a Reasoning Engine holdsAt ( F , T + 1 ) ← initiatedAt F , T ) holdsAtAt ( F , T + 1 ) ← holdsAt ( F , T ) , not terminatedAt ( F , T ) . Very efficient inference: Artikis et al. An Event Calculus for Event Recognition, TKDE, 2015. Input ◮ Recognition ◮ Output � . . . . . . . . . . . . Event Simple Events Recognition Complex Events System . . . . . . . . . . . . Complex Event happensAt ( active ( id 0 ) , 10 ) holdsAt ( coord ( id 0 , 20 . 88 , 11 . 90 ) , 10 ) Definitions happensAt ( active ( id 1 ) , 10 ) holdsAt ( coord ( id 1 , 22 . 34 , 15 . 23 ) , 10 ) holdsAt ( meet ( id 0 , id 1 ) , 11 ) holdsAt ( meet ( id 0 , id 1 ) , 12 ) . . . holdsAt ( meet ( id 0 , id 1 ) , 13 ) initiatedAt ( meet ( X , Y ) , T ) ← . . . happensAt ( active ( X ) , T ) , happensAt ( active ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . Learn this terminatedAt ( meet ( X , Y ) , T ) ← happensAt ( walking ( X ) , T ) , not holdsAt ( close ( X , Y , 25 ) , T ) . From These 5/19

The problem Setting Event Calculus as a Reasoning Engine holdsAt ( F , T + 1 ) ← initiatedAt F , T ) holdsAtAt ( F , T + 1 ) ← holdsAt ( F , T ) , not terminatedAt ( F , T ) . Very efficient inference: Artikis et al. An Event Calculus for Event Recognition, TKDE, 2015. Input ◮ Recognition ◮ Output � . . . . . . . . . . . . Event Simple Events Recognition Complex Events System . . . . . . . . . . . . Complex Event happensAt ( active ( id 0 ) , 10 ) holdsAt ( coord ( id 0 , 20 . 88 , 11 . 90 ) , 10 ) Definitions happensAt ( active ( id 1 ) , 10 ) holdsAt ( coord ( id 1 , 22 . 34 , 15 . 23 ) , 10 ) holdsAt ( meet ( id 0 , id 1 ) , 11 ) holdsAt ( meet ( id 0 , id 1 ) , 12 ) . . . holdsAt ( meet ( id 0 , id 1 ) , 13 ) initiatedAt ( meet ( X , Y ) , T ) ← . . . happensAt ( active ( X ) , T ) , happensAt ( active ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . Learn this terminatedAt ( meet ( X , Y ) , T ) ← happensAt ( walking ( X ) , T ) , From These not holdsAt ( close ( X , Y , 25 ) , T ) . 6/19

Learning Requirements ◮ Event recognition applications deal with noisy data streams. ◮ Resilience to noise → Statistical Relational Learning. ◮ Learning should be online. ◮ Single-pass. ◮ Learn from past mistakes. 7/19

Contribution of this Work Two online learners from previous work: ◮ OLED ◮ Katzouris N. et al. Online Learning of Event Definitions, TPLP , 2016. ◮ ✓ Efficient structure learning using Hoeffding bounds. ◮ ✗ Crisp learner. ◮ OSL α ◮ Micheloudakis V., et al. OSLa: Online Structure Learning using Background Knowledge Axiomatization, ECML , 2016. ◮ MLN learner. ◮ ✓ Efficient weight learning. ◮ ✗ Inefficient structure learning. ◮ Blindly generates too many rules. Current work: ◮ WoLED (OLED + weight learning) ◮ MLN learner ◮ ✓ Efficient structure learning. ◮ ✓ Efficient weight learning. 8/19

OLED initiatedAt ( meet ( X , Y ) , T ) ← 1 1 Used O ( ǫ 2 ln ) examples δ initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← ... happensAt ( active ( X ) , T ) . happensAt ( inactive ( Y ) , T ) . holdsAt ( orientation ( X , Y , 45 ) , T 1 1 Used O ( ǫ 2 ln ) examples δ initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← happensAt ( active ( X ) , T ) , happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) . holdsAt ( close ( X , Y , 25 ) , T ) . 1 1 Used O ( ǫ 2 ln ) examples initiatedAt ( meet ( X , Y ) , T ) ← δ happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . . . . . . . . . . . . . initiatedAt ( meet ( X , Y ) , T ) ← happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) , holdsAt ( close ( Y , X , 25 ) , T ) , not happensAt ( inactive ( X ) , T ) , not happensAt ( abrupt ( X ) , T ) , Bottom Clause ⊥ : not happensAt ( running ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , not happensAt ( active ( Y ) , T ) , not happensAt ( running ( Y ) , T ) , not happensAt ( abrupt ( Y ) , T ) , holdsAt ( orientation ( X , Y , 45 ) , T ) . ◮ Learns a rule with online hill-climbing. 9/19

OLED initiatedAt ( meet ( X , Y ) , T ) ← 1 1 Used O ( ǫ 2 ln ) examples δ initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← ... happensAt ( active ( X ) , T ) . happensAt ( inactive ( Y ) , T ) . holdsAt ( orientation ( X , Y , 45 ) , T 1 1 Used O ( ǫ 2 ln ) examples δ initiatedAt ( meet ( X , Y ) , T ) ← initiatedAt ( meet ( X , Y ) , T ) ← happensAt ( active ( X ) , T ) , happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) . holdsAt ( close ( X , Y , 25 ) , T ) . 1 1 Used O ( ǫ 2 ln ) examples initiatedAt ( meet ( X , Y ) , T ) ← δ happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) . . . . . . . . . . . . . initiatedAt ( meet ( X , Y ) , T ) ← happensAt ( active ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , holdsAt ( close ( X , Y , 25 ) , T ) , holdsAt ( close ( Y , X , 25 ) , T ) , not happensAt ( inactive ( X ) , T ) , not happensAt ( abrupt ( X ) , T ) , Bottom Clause ⊥ : not happensAt ( running ( X ) , T ) , happensAt ( inactive ( Y ) , T ) , not happensAt ( active ( Y ) , T ) , not happensAt ( running ( Y ) , T ) , not happensAt ( abrupt ( Y ) , T ) , holdsAt ( orientation ( X , Y , 45 ) , T ) . ◮ Uses Hoeffding tests to make ( ǫ, δ )-optimal decisions. 10/19