SlideShare a Scribd company logo
Automating the Formalization of Product Comparison Matrices 
Guillaume Bécan, Nicolas Sannier, Mathieu Acher, Olivier Barais, Arnaud Blouin, Benoit Baudry
Product lines everywhere 
Automating the Formalization of Product Comparison Matrices 
- 2
Product Comparison Matrices (PCMs) 
Automating the Formalization of Product Comparison Matrices 
- 3
Services on top of PCMs 
Automating the Formalization of Product Comparison Matrices 
- 4 
Edit 
Compare 
Visualize 
Filter 
Rank 
Merge 
Configure 
Multi-objective optimization
Problem 
Automating the Formalization of Product Comparison Matrices 
- 5 
Edit 
Compare 
Visualize 
… 
Information is: 
•Uncontrolled 
•Heterogeneous 
•Ambiguous 
[Sannier et al, ASE 2013] 
| [[Acer Inc.|Acer]] 
| [[Acer beTouch E110|beTouch E110]] 
| {{dts|format=dmy|2010|2|15}} 
| 1.5 
| [[320x240|320x240 QVGA]] 
| {{convert|2.8|in|mm|abbr=on}} 
| Touch, accelerometer 
| 
* [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] 
* [[Universal Mobile Telecommunications System|UMTS]] 850 1900 
* CSD
Problem 
Automating the Formalization of Product Comparison Matrices 
- 6 
Common 
language 
Transformation 
Edit 
Compare 
Visualize 
… 
•How to formalize data contained in natural language PCMs? 
•How to automate the formalization of PCMs? 
•What tools and services can be built on top of this formalization?
Contributions 
Automating the Formalization of Product Comparison Matrices 
- 7 
1.Design of a metamodel for product comparison matrices 
2.Automated techniques for formalizing raw data into formalized product comparison matrix model 
3.Evaluation on 30,000+ cells from Wikipedia
Metamodeling driven by (lots of) data 
Automating the Formalization of Product Comparison Matrices 
- 8 
Working on the metamodel since February 2013 
300+ PCMs – 300,000 cells 
Numerous domains 
Manual review of 50 PCMs (thousands of cells) 
Statistics on all PCMs 
Analysis of Wikipedia syntax for tables 
Automated transformation of all PCMs to PCM models
PCM metamodel 
Automating the Formalization of Product Comparison Matrices 
- 9
PCM metamodel 
Automating the Formalization of Product Comparison Matrices 
- 10 
Structure of a PCM
PCM metamodel 
Automating the Formalization of Product Comparison Matrices 
- 11 
Feature/Product oriented
Automating the Formalization of Product Comparison Matrices 
- 12 
Formalized interpretation of a cell 
Data types: Boolean, Integer, Real 
Special values: Unknown, Empty, Inconsistent, Partial 
PCM metamodel 
row string 
formalized integer
Contributions 
Automating the Formalization of Product Comparison Matrices 
- 13 
1.Design of a metamodel for product comparison matrices 
2.Automated techniques for formalizing raw data into formalized product comparison matrix model 
3.Evaluation on 30,000+ cells from Wikipedia
Approach 
Automating the Formalization of Product Comparison Matrices 
- 14 
Parsing: transform a PCM artefact in a PCM model 
PCM 
PCM model 
parsing 
preprocessing 
extracting 
information 
exploiting 
PCM model 
PCM model 
PCM metamodel 
S 
E 
R 
V 
I 
C 
E 
S 
| [[Acer Inc.|Acer]] 
| [[Acer beTouch E110|beTouch E110]] 
| {{dts|format=dmy|2010|2|15}} 
| 1.5 
| [[320x240|320x240 QVGA]] 
| {{convert|2.8|in|mm|abbr=on}} 
| Touch, accelerometer 
| 
* [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] 
* [[Universal Mobile Telecommunications System|UMTS]] 850 1900 
* CSD 
Enable the development of a generic formalization process
Approach 
Automating the Formalization of Product Comparison Matrices 
- 15 
Preprocessing: 
Contributors cannot be trusted: missing cells, headers everywhere 
We have to normalize the matrix and identify headers 
Default strategy: first line and first column are headers 
PCM 
PCM model 
parsing 
preprocessing 
extracting 
information 
exploiting 
PCM model 
PCM model 
PCM metamodel 
S 
E 
R 
V 
I 
C 
E 
S
Approach 
Automating the Formalization of Product Comparison Matrices 
- 16 
Extracting information: 
•Identify features and products 
•Interpret cells based on a set of syntactic rules (regex) 
PCM 
PCM model 
parsing 
preprocessing 
extracting 
information 
exploiting 
PCM model 
PCM model 
PCM metamodel 
S 
E 
R 
V 
I 
C 
E 
S 
List of rules: … "d+" => Integer … 
match 
Integer(100) 
Same process as the metamodel for creating the rules
Contributions 
Automating the Formalization of Product Comparison Matrices 
- 17 
1.Design of a metamodel for product comparison matrices 
2.Automated techniques for formalizing raw data into formalized product comparison matrix model 
3.Evaluation on 30,000+ cells from Wikipedia
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 18 
Experimental settings: 
•75 PCMs from Wikipedia 
•Headers specified manually 
•Automated extraction of information 
PCM 
PCM model 
parsing 
preprocessing 
extracting 
information 
PCM model 
PCM model 
PCM metamodel 
exploiting 
S 
E 
R 
V 
I 
C 
E 
S 
RQ1 
RQ2 
RQ3
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 19 
Task: check interpretation of each cell (30,000+) 
•Validate 
•Correct it with existing concept 
•Correct it with a new concept 
•I don’t know / there is no interpretation 
20 evaluators 
Online editor
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 20 
Metrics: 
•Number of valid cells 
•Number of cells corrected with concepts from the metamodel 
•Number of cells corrected with new concepts 
•List of new concepts
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 21 
RQ1: To what extent can PCMs be formalized? 
93.11% of the cells are valid 
2.61% are corrected with concepts from the metamodel 
4.28% are invalid and the evaluators proposed a new concept 
•Dates 
•Dimensions and units 
•Versions 
Solution: 
•Add corresponding data types to the metamodel 
•Create new rules for interpreting cells
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 22 
RQ2: To what extent can the formalization be automated? 
93,11% of the cells are correctly formalized 
Formalization errors may arise from 4 main areas: 
•Overlapping concepts (e.g. what does an empty cell mean?) 
•Missing concepts (e.g. dates, versions…) 
•Missing interpretation rules 
•Bad rules
Evaluation 
Automating the Formalization of Product Comparison Matrices 
- 23 
RQ3: What services can be built on top of formalized PCMs? 
Editing and formalizing PCMs Warnings during edition (inconsistent cells) Filtering capabilities Translate PCMs to variability models 
The metamodel provides 
•Feature/product oriented perspective 
•Clear semantics
Results of the evaluation 
Automating the Formalization of Product Comparison Matrices 
- 24 
We now have a common language for PCMs 
•validated by humans 
•validated by transformation 
•validated by the editor 
A large proportion of the formalization can be automated 
BUT human is necessary 
Good news: the editor can help formalizing the data
Future work 
Automating the Formalization of Product Comparison Matrices 
- 26 
Universal editor 
Support large datasets 
Community of PCM contributors 
Synchronization with Wikipedia
Questions? 
Automating the Formalization of Product Comparison Matrices 
- 27 
PCM 
PCM model 
parsing 
preprocessing 
extracting 
information 
exploiting 
PCM model 
PCM model 
PCM metamodel 
S 
E 
R 
V 
I 
C 
E 
S

More Related Content

What's hot

CIS110 Computer Programming Design Chapter (7)
CIS110 Computer Programming Design Chapter  (7)CIS110 Computer Programming Design Chapter  (7)
CIS110 Computer Programming Design Chapter (7)
Dr. Ahmed Al Zaidy
 
Programming Logic and Design: Working with Data
Programming Logic and Design: Working with DataProgramming Logic and Design: Working with Data
Programming Logic and Design: Working with Data
Nicole Ryan
 
Machine learning with scikitlearn
Machine learning with scikitlearnMachine learning with scikitlearn
Machine learning with scikitlearn
Pratap Dangeti
 
CIS110 Computer Programming Design Chapter (10)
CIS110 Computer Programming Design Chapter  (10)CIS110 Computer Programming Design Chapter  (10)
CIS110 Computer Programming Design Chapter (10)
Dr. Ahmed Al Zaidy
 
CIS110 Computer Programming Design Chapter (13)
CIS110 Computer Programming Design Chapter  (13)CIS110 Computer Programming Design Chapter  (13)
CIS110 Computer Programming Design Chapter (13)
Dr. Ahmed Al Zaidy
 
Building largescalepredictionsystemv1
Building largescalepredictionsystemv1Building largescalepredictionsystemv1
Building largescalepredictionsystemv1
arthi v
 
Logic Formulation 3
Logic Formulation 3Logic Formulation 3
Logic Formulation 3
deathful
 
Feature Selection Techniques for Software Fault Prediction (Summary)
Feature Selection Techniques for Software Fault Prediction (Summary)Feature Selection Techniques for Software Fault Prediction (Summary)
Feature Selection Techniques for Software Fault Prediction (Summary)
SungdoGu
 
Chapter 12 Lecture: GUI Programming, Multithreading, and Animation
Chapter 12 Lecture: GUI Programming, Multithreading, and AnimationChapter 12 Lecture: GUI Programming, Multithreading, and Animation
Chapter 12 Lecture: GUI Programming, Multithreading, and Animation
Nicole Ryan
 
Decision Support Analyss for Software Effort Estimation by Analogy
Decision Support Analyss for Software Effort Estimation by AnalogyDecision Support Analyss for Software Effort Estimation by Analogy
Decision Support Analyss for Software Effort Estimation by Analogy
Tim Menzies
 
Decision table
Decision tableDecision table
Decision table
jeebala
 
Circuit analysis i with matlab computing and simulink sim powersystems modeling
Circuit analysis i with matlab computing and simulink sim powersystems modelingCircuit analysis i with matlab computing and simulink sim powersystems modeling
Circuit analysis i with matlab computing and simulink sim powersystems modeling
Indra S Wahyudi
 
Pycon2015 scope
Pycon2015 scopePycon2015 scope
Pycon2015 scope
arthi v
 

What's hot (13)

CIS110 Computer Programming Design Chapter (7)
CIS110 Computer Programming Design Chapter  (7)CIS110 Computer Programming Design Chapter  (7)
CIS110 Computer Programming Design Chapter (7)
 
Programming Logic and Design: Working with Data
Programming Logic and Design: Working with DataProgramming Logic and Design: Working with Data
Programming Logic and Design: Working with Data
 
Machine learning with scikitlearn
Machine learning with scikitlearnMachine learning with scikitlearn
Machine learning with scikitlearn
 
CIS110 Computer Programming Design Chapter (10)
CIS110 Computer Programming Design Chapter  (10)CIS110 Computer Programming Design Chapter  (10)
CIS110 Computer Programming Design Chapter (10)
 
CIS110 Computer Programming Design Chapter (13)
CIS110 Computer Programming Design Chapter  (13)CIS110 Computer Programming Design Chapter  (13)
CIS110 Computer Programming Design Chapter (13)
 
Building largescalepredictionsystemv1
Building largescalepredictionsystemv1Building largescalepredictionsystemv1
Building largescalepredictionsystemv1
 
Logic Formulation 3
Logic Formulation 3Logic Formulation 3
Logic Formulation 3
 
Feature Selection Techniques for Software Fault Prediction (Summary)
Feature Selection Techniques for Software Fault Prediction (Summary)Feature Selection Techniques for Software Fault Prediction (Summary)
Feature Selection Techniques for Software Fault Prediction (Summary)
 
Chapter 12 Lecture: GUI Programming, Multithreading, and Animation
Chapter 12 Lecture: GUI Programming, Multithreading, and AnimationChapter 12 Lecture: GUI Programming, Multithreading, and Animation
Chapter 12 Lecture: GUI Programming, Multithreading, and Animation
 
Decision Support Analyss for Software Effort Estimation by Analogy
Decision Support Analyss for Software Effort Estimation by AnalogyDecision Support Analyss for Software Effort Estimation by Analogy
Decision Support Analyss for Software Effort Estimation by Analogy
 
Decision table
Decision tableDecision table
Decision table
 
Circuit analysis i with matlab computing and simulink sim powersystems modeling
Circuit analysis i with matlab computing and simulink sim powersystems modelingCircuit analysis i with matlab computing and simulink sim powersystems modeling
Circuit analysis i with matlab computing and simulink sim powersystems modeling
 
Pycon2015 scope
Pycon2015 scopePycon2015 scope
Pycon2015 scope
 

Similar to Automating the Formalization of Product Comparison Matrices

ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdfES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
Minh Nguyen
 
CAD/CAM -PPT UNIT NO-I
CAD/CAM -PPT UNIT NO-ICAD/CAM -PPT UNIT NO-I
CAD/CAM -PPT UNIT NO-I
MalothHeeralal
 
20220914-MBT-Experiences-SB1-final.pptx
20220914-MBT-Experiences-SB1-final.pptx20220914-MBT-Experiences-SB1-final.pptx
20220914-MBT-Experiences-SB1-final.pptx
Minh Nguyen
 
Modelon Modelica executable requirements Ansys Conference 2016
Modelon Modelica executable requirements Ansys Conference 2016Modelon Modelica executable requirements Ansys Conference 2016
Modelon Modelica executable requirements Ansys Conference 2016
Modelon
 
CIM unit-1
CIM  unit-1CIM  unit-1
CIM unit-1
Dr.PERIASAMY K
 
Automotive engineering design - Model Based Design
Automotive engineering design - Model Based DesignAutomotive engineering design - Model Based Design
Automotive engineering design - Model Based Design
Vinayagam Mariappan
 
Presentation Verification & Validation
Presentation Verification & ValidationPresentation Verification & Validation
Presentation Verification & Validation
Elmar Selbach
 
Feedback Strategy for Closed-loop Inspection Based on STEP-NC
Feedback Strategy for Closed-loop Inspection Based on STEP-NCFeedback Strategy for Closed-loop Inspection Based on STEP-NC
Feedback Strategy for Closed-loop Inspection Based on STEP-NC
Cristhian Riaño Jaimes
 
An Integrated Simulation Tool Framework for Process Data Management
An Integrated Simulation Tool Framework for Process Data ManagementAn Integrated Simulation Tool Framework for Process Data Management
An Integrated Simulation Tool Framework for Process Data Management
Cognizant
 
Guiding through a typical Machine Learning Pipeline
Guiding through a typical Machine Learning PipelineGuiding through a typical Machine Learning Pipeline
Guiding through a typical Machine Learning Pipeline
Michael Gerke
 
Critical parameter management
Critical parameter managementCritical parameter management
Critical parameter management
Cognition Corporation
 
Customer choice probabilities
Customer choice probabilitiesCustomer choice probabilities
Customer choice probabilities
Allan D. Butler
 
QDM WEB System -- Connect your suppliers and global enterprise
QDM WEB System -- Connect your suppliers and global enterpriseQDM WEB System -- Connect your suppliers and global enterprise
QDM WEB System -- Connect your suppliers and global enterprise
Benjamin Reese
 
Intro to LV in 3 Hours for Control and Sim 8_5.pptx
Intro to LV in 3 Hours for Control and Sim 8_5.pptxIntro to LV in 3 Hours for Control and Sim 8_5.pptx
Intro to LV in 3 Hours for Control and Sim 8_5.pptx
DeepakJangid87
 
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September London
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September LondonIcon solutions presentation - Pure Hybrid Cloud Event, 11th September London
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September London
IBM Systems UKI
 
Syllabus cim
Syllabus cimSyllabus cim
Syllabus cim
Prashanth J
 
Modeling and Testing Dovetail in MagicDraw
Modeling and Testing Dovetail in MagicDrawModeling and Testing Dovetail in MagicDraw
Modeling and Testing Dovetail in MagicDraw
Gregory Solovey
 
Model-Based Design For Motor Control Development
Model-Based Design For Motor Control DevelopmentModel-Based Design For Motor Control Development
Model-Based Design For Motor Control Development
The Hartford
 
B Kindilien Finding Efficiency In Mach 120408
B Kindilien Finding Efficiency In Mach 120408B Kindilien Finding Efficiency In Mach 120408
B Kindilien Finding Efficiency In Mach 120408
jgIpotiwon
 
Final
FinalFinal

Similar to Automating the Formalization of Product Comparison Matrices (20)

ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdfES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
ES2022-Minh-Nguyen-ShapingTestsIntoModelsForAutomatedTCGeneration.pdf
 
CAD/CAM -PPT UNIT NO-I
CAD/CAM -PPT UNIT NO-ICAD/CAM -PPT UNIT NO-I
CAD/CAM -PPT UNIT NO-I
 
20220914-MBT-Experiences-SB1-final.pptx
20220914-MBT-Experiences-SB1-final.pptx20220914-MBT-Experiences-SB1-final.pptx
20220914-MBT-Experiences-SB1-final.pptx
 
Modelon Modelica executable requirements Ansys Conference 2016
Modelon Modelica executable requirements Ansys Conference 2016Modelon Modelica executable requirements Ansys Conference 2016
Modelon Modelica executable requirements Ansys Conference 2016
 
CIM unit-1
CIM  unit-1CIM  unit-1
CIM unit-1
 
Automotive engineering design - Model Based Design
Automotive engineering design - Model Based DesignAutomotive engineering design - Model Based Design
Automotive engineering design - Model Based Design
 
Presentation Verification & Validation
Presentation Verification & ValidationPresentation Verification & Validation
Presentation Verification & Validation
 
Feedback Strategy for Closed-loop Inspection Based on STEP-NC
Feedback Strategy for Closed-loop Inspection Based on STEP-NCFeedback Strategy for Closed-loop Inspection Based on STEP-NC
Feedback Strategy for Closed-loop Inspection Based on STEP-NC
 
An Integrated Simulation Tool Framework for Process Data Management
An Integrated Simulation Tool Framework for Process Data ManagementAn Integrated Simulation Tool Framework for Process Data Management
An Integrated Simulation Tool Framework for Process Data Management
 
Guiding through a typical Machine Learning Pipeline
Guiding through a typical Machine Learning PipelineGuiding through a typical Machine Learning Pipeline
Guiding through a typical Machine Learning Pipeline
 
Critical parameter management
Critical parameter managementCritical parameter management
Critical parameter management
 
Customer choice probabilities
Customer choice probabilitiesCustomer choice probabilities
Customer choice probabilities
 
QDM WEB System -- Connect your suppliers and global enterprise
QDM WEB System -- Connect your suppliers and global enterpriseQDM WEB System -- Connect your suppliers and global enterprise
QDM WEB System -- Connect your suppliers and global enterprise
 
Intro to LV in 3 Hours for Control and Sim 8_5.pptx
Intro to LV in 3 Hours for Control and Sim 8_5.pptxIntro to LV in 3 Hours for Control and Sim 8_5.pptx
Intro to LV in 3 Hours for Control and Sim 8_5.pptx
 
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September London
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September LondonIcon solutions presentation - Pure Hybrid Cloud Event, 11th September London
Icon solutions presentation - Pure Hybrid Cloud Event, 11th September London
 
Syllabus cim
Syllabus cimSyllabus cim
Syllabus cim
 
Modeling and Testing Dovetail in MagicDraw
Modeling and Testing Dovetail in MagicDrawModeling and Testing Dovetail in MagicDraw
Modeling and Testing Dovetail in MagicDraw
 
Model-Based Design For Motor Control Development
Model-Based Design For Motor Control DevelopmentModel-Based Design For Motor Control Development
Model-Based Design For Motor Control Development
 
B Kindilien Finding Efficiency In Mach 120408
B Kindilien Finding Efficiency In Mach 120408B Kindilien Finding Efficiency In Mach 120408
B Kindilien Finding Efficiency In Mach 120408
 
Final
FinalFinal
Final
 

Recently uploaded

The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
Sérgio Sacani
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
PirithiRaju
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
PirithiRaju
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR
 
Compexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titrationCompexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titration
Vandana Devesh Sharma
 
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Sérgio Sacani
 
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfMending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Selcen Ozturkcan
 
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
Advanced-Concepts-Team
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
PirithiRaju
 
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
Scintica Instrumentation
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
International Food Policy Research Institute- South Asia Office
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
ABHISHEK SONI NIMT INSTITUTE OF MEDICAL AND PARAMEDCIAL SCIENCES , GOVT PG COLLEGE NOIDA
 
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
PsychoTech Services
 
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdfHUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
Ritik83251
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
Leonel Morgado
 
fermented food science of sauerkraut.pptx
fermented food science of sauerkraut.pptxfermented food science of sauerkraut.pptx
fermented food science of sauerkraut.pptx
ananya23nair
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
fatima132662
 
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
hozt8xgk
 
Clinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdfClinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdf
RAYMUNDONAVARROCORON
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
RDhivya6
 

Recently uploaded (20)

The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
 
Compexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titrationCompexometric titration/Chelatorphy titration/chelating titration
Compexometric titration/Chelatorphy titration/chelating titration
 
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
 
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfMending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
 
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
 
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
 
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
 
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdfHUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
 
fermented food science of sauerkraut.pptx
fermented food science of sauerkraut.pptxfermented food science of sauerkraut.pptx
fermented food science of sauerkraut.pptx
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
 
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
 
Clinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdfClinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdf
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
 

Automating the Formalization of Product Comparison Matrices

  • 1. Automating the Formalization of Product Comparison Matrices Guillaume Bécan, Nicolas Sannier, Mathieu Acher, Olivier Barais, Arnaud Blouin, Benoit Baudry
  • 2. Product lines everywhere Automating the Formalization of Product Comparison Matrices - 2
  • 3. Product Comparison Matrices (PCMs) Automating the Formalization of Product Comparison Matrices - 3
  • 4. Services on top of PCMs Automating the Formalization of Product Comparison Matrices - 4 Edit Compare Visualize Filter Rank Merge Configure Multi-objective optimization
  • 5. Problem Automating the Formalization of Product Comparison Matrices - 5 Edit Compare Visualize … Information is: •Uncontrolled •Heterogeneous •Ambiguous [Sannier et al, ASE 2013] | [[Acer Inc.|Acer]] | [[Acer beTouch E110|beTouch E110]] | {{dts|format=dmy|2010|2|15}} | 1.5 | [[320x240|320x240 QVGA]] | {{convert|2.8|in|mm|abbr=on}} | Touch, accelerometer | * [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] * [[Universal Mobile Telecommunications System|UMTS]] 850 1900 * CSD
  • 6. Problem Automating the Formalization of Product Comparison Matrices - 6 Common language Transformation Edit Compare Visualize … •How to formalize data contained in natural language PCMs? •How to automate the formalization of PCMs? •What tools and services can be built on top of this formalization?
  • 7. Contributions Automating the Formalization of Product Comparison Matrices - 7 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  • 8. Metamodeling driven by (lots of) data Automating the Formalization of Product Comparison Matrices - 8 Working on the metamodel since February 2013 300+ PCMs – 300,000 cells Numerous domains Manual review of 50 PCMs (thousands of cells) Statistics on all PCMs Analysis of Wikipedia syntax for tables Automated transformation of all PCMs to PCM models
  • 9. PCM metamodel Automating the Formalization of Product Comparison Matrices - 9
  • 10. PCM metamodel Automating the Formalization of Product Comparison Matrices - 10 Structure of a PCM
  • 11. PCM metamodel Automating the Formalization of Product Comparison Matrices - 11 Feature/Product oriented
  • 12. Automating the Formalization of Product Comparison Matrices - 12 Formalized interpretation of a cell Data types: Boolean, Integer, Real Special values: Unknown, Empty, Inconsistent, Partial PCM metamodel row string formalized integer
  • 13. Contributions Automating the Formalization of Product Comparison Matrices - 13 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  • 14. Approach Automating the Formalization of Product Comparison Matrices - 14 Parsing: transform a PCM artefact in a PCM model PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S | [[Acer Inc.|Acer]] | [[Acer beTouch E110|beTouch E110]] | {{dts|format=dmy|2010|2|15}} | 1.5 | [[320x240|320x240 QVGA]] | {{convert|2.8|in|mm|abbr=on}} | Touch, accelerometer | * [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] * [[Universal Mobile Telecommunications System|UMTS]] 850 1900 * CSD Enable the development of a generic formalization process
  • 15. Approach Automating the Formalization of Product Comparison Matrices - 15 Preprocessing: Contributors cannot be trusted: missing cells, headers everywhere We have to normalize the matrix and identify headers Default strategy: first line and first column are headers PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S
  • 16. Approach Automating the Formalization of Product Comparison Matrices - 16 Extracting information: •Identify features and products •Interpret cells based on a set of syntactic rules (regex) PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S List of rules: … "d+" => Integer … match Integer(100) Same process as the metamodel for creating the rules
  • 17. Contributions Automating the Formalization of Product Comparison Matrices - 17 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  • 18. Evaluation Automating the Formalization of Product Comparison Matrices - 18 Experimental settings: •75 PCMs from Wikipedia •Headers specified manually •Automated extraction of information PCM PCM model parsing preprocessing extracting information PCM model PCM model PCM metamodel exploiting S E R V I C E S RQ1 RQ2 RQ3
  • 19. Evaluation Automating the Formalization of Product Comparison Matrices - 19 Task: check interpretation of each cell (30,000+) •Validate •Correct it with existing concept •Correct it with a new concept •I don’t know / there is no interpretation 20 evaluators Online editor
  • 20. Evaluation Automating the Formalization of Product Comparison Matrices - 20 Metrics: •Number of valid cells •Number of cells corrected with concepts from the metamodel •Number of cells corrected with new concepts •List of new concepts
  • 21. Evaluation Automating the Formalization of Product Comparison Matrices - 21 RQ1: To what extent can PCMs be formalized? 93.11% of the cells are valid 2.61% are corrected with concepts from the metamodel 4.28% are invalid and the evaluators proposed a new concept •Dates •Dimensions and units •Versions Solution: •Add corresponding data types to the metamodel •Create new rules for interpreting cells
  • 22. Evaluation Automating the Formalization of Product Comparison Matrices - 22 RQ2: To what extent can the formalization be automated? 93,11% of the cells are correctly formalized Formalization errors may arise from 4 main areas: •Overlapping concepts (e.g. what does an empty cell mean?) •Missing concepts (e.g. dates, versions…) •Missing interpretation rules •Bad rules
  • 23. Evaluation Automating the Formalization of Product Comparison Matrices - 23 RQ3: What services can be built on top of formalized PCMs? Editing and formalizing PCMs Warnings during edition (inconsistent cells) Filtering capabilities Translate PCMs to variability models The metamodel provides •Feature/product oriented perspective •Clear semantics
  • 24. Results of the evaluation Automating the Formalization of Product Comparison Matrices - 24 We now have a common language for PCMs •validated by humans •validated by transformation •validated by the editor A large proportion of the formalization can be automated BUT human is necessary Good news: the editor can help formalizing the data
  • 25. Future work Automating the Formalization of Product Comparison Matrices - 26 Universal editor Support large datasets Community of PCM contributors Synchronization with Wikipedia
  • 26. Questions? Automating the Formalization of Product Comparison Matrices - 27 PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S