SlideShare une entreprise Scribd logo
1  sur  36
Fast ALS-based matrix factorization for explicit and implicit feedback datasets Istv á n Pil á szy, D ávid Zibriczky,  Domonkos Tikk Gravity R&D Ltd. www.gravityrd.com 28   September  20 10
Collaborative filtering
Problem setting 5 4 3 4 4 2 4 1
[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],P T R T Q
Matrix Factorization  for explicit feedb. Q P 5 5 4 3 1 R 3.3 1.3 1.3 1. 4 1. 3 1 . 9 1. 7 0.7 1.0 1.3 0.8 0 0. 7 0.4 1. 7 0. 3 2.1 2.2 6.7 1.6 1. 4 2 4 3.3 1.6 1.8
Finding P and Q Q P R 0.3 0.9 0.7 1.3 0.5 0 .6 1.2 0.3 1. 6 1.1 5 5 4 3 1 2 4 ? ? ,[object Object],[object Object]
Finding  p 1  with RR ,[object Object]
Finding  p 1  with RR Q P R 0.3 0.9 0.7 1.3 0.5 0 .6 1.2 0.3 1. 6 1.1 5 5 4 3 1 2 4 2.3 3.2
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Implicit feedback Q P 1 0 R 0.5 0.1 0.2 0.7 0.3 0.1 0.1 0.7 0.3 0 0.2 0 0. 7 0.4 0.4 0. 4 1 0 0 0 0 1 1 0 0 1 0 1 1
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object]
Conclusions users items ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for your attention ?

Contenu connexe

Tendances

Lecture 2 fuzzy inference system
Lecture 2  fuzzy inference systemLecture 2  fuzzy inference system
Lecture 2 fuzzy inference systemParveenMalik18
 
Lecture 6 radial basis-function_network
Lecture 6 radial basis-function_networkLecture 6 radial basis-function_network
Lecture 6 radial basis-function_networkParveenMalik18
 
Multiclass Logistic Regression: Derivation and Apache Spark Examples
Multiclass Logistic Regression: Derivation and Apache Spark ExamplesMulticlass Logistic Regression: Derivation and Apache Spark Examples
Multiclass Logistic Regression: Derivation and Apache Spark ExamplesMarjan Sterjev
 
MediaEval 2015 - Emotion in Music: Task Overview
MediaEval 2015 - Emotion in Music: Task OverviewMediaEval 2015 - Emotion in Music: Task Overview
MediaEval 2015 - Emotion in Music: Task Overviewmultimediaeval
 
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님AI Robotics KR
 
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]AI Robotics KR
 
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]AI Robotics KR
 
"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest
"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest
"Speech recognition" - Hidden Markov Models @ Papers We Love BucharestStefan Adam
 
Gradient Estimation Using Stochastic Computation Graphs
Gradient Estimation Using Stochastic Computation GraphsGradient Estimation Using Stochastic Computation Graphs
Gradient Estimation Using Stochastic Computation GraphsYoonho Lee
 
0415_seminar_DeepDPG
0415_seminar_DeepDPG0415_seminar_DeepDPG
0415_seminar_DeepDPGHye-min Ahn
 
Applied Machine Learning For Search Engine Relevance
Applied Machine Learning For Search Engine Relevance Applied Machine Learning For Search Engine Relevance
Applied Machine Learning For Search Engine Relevance charlesmartin14
 

Tendances (14)

Lecture 2 fuzzy inference system
Lecture 2  fuzzy inference systemLecture 2  fuzzy inference system
Lecture 2 fuzzy inference system
 
Lecture 6 radial basis-function_network
Lecture 6 radial basis-function_networkLecture 6 radial basis-function_network
Lecture 6 radial basis-function_network
 
Multiclass Logistic Regression: Derivation and Apache Spark Examples
Multiclass Logistic Regression: Derivation and Apache Spark ExamplesMulticlass Logistic Regression: Derivation and Apache Spark Examples
Multiclass Logistic Regression: Derivation and Apache Spark Examples
 
MediaEval 2015 - Emotion in Music: Task Overview
MediaEval 2015 - Emotion in Music: Task OverviewMediaEval 2015 - Emotion in Music: Task Overview
MediaEval 2015 - Emotion in Music: Task Overview
 
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님
Bayesian Inference : Kalman filter 에서 Optimization 까지 - 김홍배 박사님
 
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]
Sensor Fusion Study - Ch15. The Particle Filter [Seoyeon Stella Yang]
 
Av 738-Adaptive Filters - Extended Kalman Filter
Av 738-Adaptive Filters - Extended Kalman FilterAv 738-Adaptive Filters - Extended Kalman Filter
Av 738-Adaptive Filters - Extended Kalman Filter
 
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]
Sensor Fusion Study - Ch3. Least Square Estimation [강소라, Stella, Hayden]
 
"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest
"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest
"Speech recognition" - Hidden Markov Models @ Papers We Love Bucharest
 
Lecture 3
Lecture 3Lecture 3
Lecture 3
 
Gradient Estimation Using Stochastic Computation Graphs
Gradient Estimation Using Stochastic Computation GraphsGradient Estimation Using Stochastic Computation Graphs
Gradient Estimation Using Stochastic Computation Graphs
 
0415_seminar_DeepDPG
0415_seminar_DeepDPG0415_seminar_DeepDPG
0415_seminar_DeepDPG
 
Applied Machine Learning For Search Engine Relevance
Applied Machine Learning For Search Engine Relevance Applied Machine Learning For Search Engine Relevance
Applied Machine Learning For Search Engine Relevance
 
ANCLMS
ANCLMSANCLMS
ANCLMS
 

Similaire à Fast ALS-based matrix factorization for explicit and implicit feedback datasets

Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...Florent Renucci
 
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6tingyuansenastro
 
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...少华 白
 
Extrapolation
ExtrapolationExtrapolation
Extrapolationcarlos
 
Extrapolation
ExtrapolationExtrapolation
Extrapolationjonathan
 
Extrapolation
ExtrapolationExtrapolation
ExtrapolationSamir
 
DIAPOSITIVA
DIAPOSITIVADIAPOSITIVA
DIAPOSITIVAArmando
 
Extrapolation
ExtrapolationExtrapolation
Extrapolationjonathan
 
Extrapolation
ExtrapolationExtrapolation
ExtrapolationJLMora
 
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...Naoki Hayashi
 
Kulum alin-11 jan2014
Kulum alin-11 jan2014Kulum alin-11 jan2014
Kulum alin-11 jan2014rolly purnomo
 

Similaire à Fast ALS-based matrix factorization for explicit and implicit feedback datasets (20)

ilp-nlp-slides.pdf
ilp-nlp-slides.pdfilp-nlp-slides.pdf
ilp-nlp-slides.pdf
 
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
 
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6
ANU ASTR 4004 / 8004 Astronomical Computing : Lecture 6
 
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...
Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implicat...
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
mm
mmmm
mm
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
DIAPOSITIVA
DIAPOSITIVADIAPOSITIVA
DIAPOSITIVA
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Extrapolation
ExtrapolationExtrapolation
Extrapolation
 
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...
Bayesian Generalization Error and Real Log Canonical Threshold in Non-negativ...
 
Kulum alin-11 jan2014
Kulum alin-11 jan2014Kulum alin-11 jan2014
Kulum alin-11 jan2014
 

Dernier

Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfSeasiaInfotech2
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...Fwdays
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clashcharlottematthew16
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024The Digital Insurer
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 

Dernier (20)

Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdf
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 

Fast ALS-based matrix factorization for explicit and implicit feedback datasets

  • 1. Fast ALS-based matrix factorization for explicit and implicit feedback datasets Istv á n Pil á szy, D ávid Zibriczky, Domonkos Tikk Gravity R&D Ltd. www.gravityrd.com 28 September 20 10
  • 3. Problem setting 5 4 3 4 4 2 4 1
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18. Matrix Factorization for explicit feedb. Q P 5 5 4 3 1 R 3.3 1.3 1.3 1. 4 1. 3 1 . 9 1. 7 0.7 1.0 1.3 0.8 0 0. 7 0.4 1. 7 0. 3 2.1 2.2 6.7 1.6 1. 4 2 4 3.3 1.6 1.8
  • 19.
  • 20.
  • 21. Finding p 1 with RR Q P R 0.3 0.9 0.7 1.3 0.5 0 .6 1.2 0.3 1. 6 1.1 5 5 4 3 1 2 4 2.3 3.2
  • 22.
  • 23.
  • 24. Implicit feedback Q P 1 0 R 0.5 0.1 0.2 0.7 0.3 0.1 0.1 0.7 0.3 0 0.2 0 0. 7 0.4 0.4 0. 4 1 0 0 0 0 1 1 0 0 1 0 1 1
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36. Thank you for your attention ?