SlideShare a Scribd company logo
1 of 42
Download to read offline
Automatic Mathematical Information
Retrieval to Perform Translations up to
Computer Algebra Systems
André Greiner-Petter*
June 6, 2018
University of Konstanz
Germany
*sponsored by SIGIR Student Travel Grant @GreinerPetter 1/9
Motivation & Problems
Motivation - Formulae Presentations DLMF 18.3
A Jacobi polynomial in different systems.
Rendered Version:
P
(α,β)
n (cos(aΘ))
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n,alpha,beta,cos(a*Theta))
CAS Mathematica:
JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]]
2/9
Motivation - Formulae Presentations DLMF 18.3
A Jacobi polynomial in different systems.
Rendered Version:
P
(α,β)
n (cos(aΘ))
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n,alpha,beta,cos(a*Theta))
CAS Mathematica:
JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]]
2/9
Motivation - Formulae Presentations DLMF 18.3
A Jacobi polynomial in different systems.
Rendered Version:
P
(α,β)
n (cos(aΘ))
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n,alpha,beta,cos(a*Theta))
CAS Mathematica:
JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]]
2/9
Motivation - Formulae Presentations DLMF 18.3
A Jacobi polynomial in different systems.
Rendered Version:
P
(α,β)
n (cos(aΘ))
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n,alpha,beta,cos(a*Theta))
CAS Mathematica:
JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]]
2/9
Presentation To Computation
with semantic information
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n, alpha, beta, cos(a*Theta))
Potential Problems:
• Differences in syntax
• Function is not implemented in one system,
• Function has multiple representations in one system,
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n, alpha, beta, cos(a*Theta))
Potential Problems:
• Differences in syntax
• Function is not implemented in one system,
• Function has multiple representations in one system,
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP($2, $0, $1, $3)
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
• Function has multiple representations in one system,
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n, alpha, beta, cos(a*Theta))
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
• Function has multiple representations in one system,
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
DLMF 18.5.7
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
translate equivalent presentations
• Function has multiple representations in one system,
• Differences in definitions.
n
=0
(n + α + β + 1) (α + + 1)n−
! (n − )!
x − 1
2
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP or Jacobi or JacobiPoly
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
translate equivalent presentations
• Function has multiple representations in one system,
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP or Jacobi or JacobiPoly
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
translate equivalent presentations
• Function has multiple representations in one system,
just pick a valid translation
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n, alpha, beta, cos(a*Theta))
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
translate equivalent presentations
• Function has multiple representations in one system,
just pick a valid translation
• Differences in definitions.
3/9
Problems of Translations DLMF 18.3
Semantic LATEX:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
CAS Maple:
JacobiP(n, alpha, beta, cos(a*Theta))
Potential Problems:
• Differences in syntax ← solved by translation patterns
• Function is not implemented in one system,
translate equivalent presentations
• Function has multiple representations in one system,
just pick a valid translation
• Differences in definitions. ← wait... What?
3/9
Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions
Rendered Version Semantic LATEX CAS Maple
arccot(z) acot@{z} arccot(z)
4/9
Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions
Rendered Version Semantic LATEX CAS Maple
arccot(z) acot@{z} arccot(z)
Maple
Figure 1: (arccot(z)) with
branch cut at [−∞i, −i], [i, ∞i].
DLMF & Mathematica
Figure 2: (arccot(z)) with
branch cut at [−i, i].
4/9
Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions
Rendered Version Semantic LATEX CAS Maple
arccot(z) acot@{z} arccot(z)
Maple
Figure 1: (arccot(z)) with
branch cut at [−∞i, −i], [i, ∞i].
DLMF & Mathematica
Figure 2: (arccot(z)) with
branch cut at [−i, i].
4/9
Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions
Rendered Version Semantic LATEX CAS Maple
arccot(z) acot@{z} arctan(1/z)
Maple
Figure 1: (arccot(z)) with
branch cut at [−∞i, −i], [i, ∞i].
DLMF & Mathematica
Figure 2: (arccot(z)) with
branch cut at [−i, i].
4/9
Presentation To Computation (P2C)
without semantic information
Problems of Generic LATEX DLMF 18.3
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantics:
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
Potential Problems:
• Is P a function, variable, constant?
• Is cos(aΘ) an argument of P or part of a multiplication?
• What are α, β, n, a, and Θ?
5/9
Problems of Generic LATEX DLMF 18.3
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantics:
Jacobi polynomial or Legendre function or Ferrers function or ...
Potential Problems:
• Is P a function, variable, constant?
• Is cos(aΘ) an argument of P or part of a multiplication?
• What are α, β, n, a, and Θ?
5/9
Problems of Generic LATEX DLMF 18.3
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantics:
P(cos(aΘ)) vs P · (cos(aΘ))
Potential Problems:
• Is P a function, variable, constant?
• Is cos(aΘ) an argument of P or part of a multiplication?
• What are α, β, n, a, and Θ?
5/9
Problems of Generic LATEX DLMF 18.3
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Semantics:
Variable or 2nd Feigenbaum constant or ...
Potential Problems:
• Is P a function, variable, constant?
• Is cos(aΘ) an argument of P or part of a multiplication?
• What are α, β, n, a, and Θ?
5/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Rendered LATEX:
P
(α,β)
n (cos(aΘ))
The Naive Approach
How does a reader understands the mathematical formula?
• he knows the symbols and structure,
knowledge-based pattern recognition
• it was previously introduced in the paper (e.g. in definitions,
the text or in other referenced publications),
analyse the context from near to far
• he searching the formula in books or online
dictionary-based pattern recognition
6/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Generic LATEX:
P_n^{(alpha,beta)}(cos(aTheta))
Adopt Human Behavior
Let’s try to adopt the previous steps
• pattern recognition
narrow down possible meanings from the structure of the
expression
• context analysis
Near-Field-Analysis (NFA), e.g., extract identifier-definien
pairs from text, analyze definition environments, ...
Far-Field-Analysis (FFA), e.g., overall topic of the paper,
citations, author’s field of interest, ...
7/9
Multiple-Scan Approach
Expression Analysis
• 1 subscript
• 2 supscripts in parentheses
• 1 variable
• The variable is a subexpression
Expression Analysis
• 1 subscript
• 2 supscripts in parentheses
• 1 variable
• The variable is a subexpression
CONCLUSION
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
Semantic LaTeX
JacobiP{alpha}{beta}{n}@{cos@{aTheta}}
Semantic LaTeX
MLPMLP
MLP Syntax TreeMLP Syntax TreeMLP Syntax Tree
P_n^{(alpha, beta)}(cos(aTheta))
Generic LaTeX
P_n^{(alpha, beta)}(cos(aTheta))
Generic LaTeX
Near-Field-Analysis
Multiple scans of
expression and its
environment
Far-Field-Analysis
8/9
Wikipedia Recommender System
A real-time recommender system for semantic
version of mathematical input included in the
editor of Wikipedia articles.
• real-time recommendations
• ordered from most likely to impossible
• consider the context
9/9
Thank you for your attention!

More Related Content

What's hot

Detecting paraphrases using recursive autoencoders
Detecting paraphrases using recursive autoencodersDetecting paraphrases using recursive autoencoders
Detecting paraphrases using recursive autoencodersFeynman Liang
 
Cs6660 compiler design may june 2016 Answer Key
Cs6660 compiler design may june 2016 Answer KeyCs6660 compiler design may june 2016 Answer Key
Cs6660 compiler design may june 2016 Answer Keyappasami
 
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQL
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQLThe DE-9IM Matrix in Details using ST_Relate: In Picture and SQL
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQLtorp42
 
Spatial Indexing
Spatial IndexingSpatial Indexing
Spatial Indexingtorp42
 
Data translation with SPARQL 1.1
Data translation with SPARQL 1.1Data translation with SPARQL 1.1
Data translation with SPARQL 1.1andreas_schultz
 
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...RuleML
 
Parallel and incremental materialisation of RDF/DATALOG in RDFOX
Parallel and incremental materialisation of RDF/DATALOG in RDFOXParallel and incremental materialisation of RDF/DATALOG in RDFOX
Parallel and incremental materialisation of RDF/DATALOG in RDFOXIoan Toma
 
Building Ontologies from Multiple Information Sources
Building Ontologies from Multiple Information SourcesBuilding Ontologies from Multiple Information Sources
Building Ontologies from Multiple Information SourcesRaji Ghawi
 
Workshop presentation hands on r programming
Workshop presentation hands on r programmingWorkshop presentation hands on r programming
Workshop presentation hands on r programmingNimrita Koul
 
RDataMining slides-r-programming
RDataMining slides-r-programmingRDataMining slides-r-programming
RDataMining slides-r-programmingYanchang Zhao
 
Data Structures and Algorithm - Week 4 - Trees, Binary Trees
Data Structures and Algorithm - Week 4 - Trees, Binary TreesData Structures and Algorithm - Week 4 - Trees, Binary Trees
Data Structures and Algorithm - Week 4 - Trees, Binary TreesFerdin Joe John Joseph PhD
 
4. Recursion - Data Structures using C++ by Varsha Patil
4. Recursion - Data Structures using C++ by Varsha Patil4. Recursion - Data Structures using C++ by Varsha Patil
4. Recursion - Data Structures using C++ by Varsha Patilwidespreadpromotion
 

What's hot (20)

Detecting paraphrases using recursive autoencoders
Detecting paraphrases using recursive autoencodersDetecting paraphrases using recursive autoencoders
Detecting paraphrases using recursive autoencoders
 
Cs6660 compiler design may june 2016 Answer Key
Cs6660 compiler design may june 2016 Answer KeyCs6660 compiler design may june 2016 Answer Key
Cs6660 compiler design may june 2016 Answer Key
 
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQL
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQLThe DE-9IM Matrix in Details using ST_Relate: In Picture and SQL
The DE-9IM Matrix in Details using ST_Relate: In Picture and SQL
 
Spatial Indexing
Spatial IndexingSpatial Indexing
Spatial Indexing
 
Introduction to R
Introduction to RIntroduction to R
Introduction to R
 
An Intoduction to R
An Intoduction to RAn Intoduction to R
An Intoduction to R
 
Data translation with SPARQL 1.1
Data translation with SPARQL 1.1Data translation with SPARQL 1.1
Data translation with SPARQL 1.1
 
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...
RuleML2015: Similarity-Based Strict Equality in a Fully Integrated Fuzzy Logi...
 
Parallel and incremental materialisation of RDF/DATALOG in RDFOX
Parallel and incremental materialisation of RDF/DATALOG in RDFOXParallel and incremental materialisation of RDF/DATALOG in RDFOX
Parallel and incremental materialisation of RDF/DATALOG in RDFOX
 
Persistent Search Trees
Persistent Search TreesPersistent Search Trees
Persistent Search Trees
 
Relational Calculus
Relational CalculusRelational Calculus
Relational Calculus
 
Building Ontologies from Multiple Information Sources
Building Ontologies from Multiple Information SourcesBuilding Ontologies from Multiple Information Sources
Building Ontologies from Multiple Information Sources
 
Data Structure
Data StructureData Structure
Data Structure
 
Workshop presentation hands on r programming
Workshop presentation hands on r programmingWorkshop presentation hands on r programming
Workshop presentation hands on r programming
 
Week 1 - Data Structures and Algorithms
Week 1 - Data Structures and AlgorithmsWeek 1 - Data Structures and Algorithms
Week 1 - Data Structures and Algorithms
 
RDataMining slides-r-programming
RDataMining slides-r-programmingRDataMining slides-r-programming
RDataMining slides-r-programming
 
Data Structures and Algorithm - Week 4 - Trees, Binary Trees
Data Structures and Algorithm - Week 4 - Trees, Binary TreesData Structures and Algorithm - Week 4 - Trees, Binary Trees
Data Structures and Algorithm - Week 4 - Trees, Binary Trees
 
4. Recursion - Data Structures using C++ by Varsha Patil
4. Recursion - Data Structures using C++ by Varsha Patil4. Recursion - Data Structures using C++ by Varsha Patil
4. Recursion - Data Structures using C++ by Varsha Patil
 
COMPUTER LABORATORY-4 LAB MANUAL BE COMPUTER ENGINEERING
COMPUTER LABORATORY-4 LAB MANUAL BE COMPUTER ENGINEERINGCOMPUTER LABORATORY-4 LAB MANUAL BE COMPUTER ENGINEERING
COMPUTER LABORATORY-4 LAB MANUAL BE COMPUTER ENGINEERING
 
Array 2011
Array 2011Array 2011
Array 2011
 

Similar to Automatic Mathematical Information Retrieval to Perform Translations up to Computer Algebra Systems

NoSQL in Perspective
NoSQL in PerspectiveNoSQL in Perspective
NoSQL in PerspectiveJeff Smith
 
Incremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesIncremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesGábor Szárnyas
 
Incremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesIncremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesopenCypher
 
Uncovering Performance Problems in Java Applications with Reference Propagati...
Uncovering Performance Problems in Java Applications with Reference Propagati...Uncovering Performance Problems in Java Applications with Reference Propagati...
Uncovering Performance Problems in Java Applications with Reference Propagati...Dacong (Tony) Yan
 
Parallel Datalog Reasoning in RDFox Presentation
Parallel Datalog Reasoning in RDFox PresentationParallel Datalog Reasoning in RDFox Presentation
Parallel Datalog Reasoning in RDFox PresentationDBOnto
 
Regular expressions
Regular expressionsRegular expressions
Regular expressionsEran Zimbler
 
A Distributed Tableau Algorithm for Package-based Description Logics
A Distributed Tableau Algorithm for Package-based Description LogicsA Distributed Tableau Algorithm for Package-based Description Logics
A Distributed Tableau Algorithm for Package-based Description LogicsJie Bao
 
Scala as a Declarative Language
Scala as a Declarative LanguageScala as a Declarative Language
Scala as a Declarative Languagevsssuresh
 
Semantic Parsing with Combinatory Categorial Grammar (CCG)
Semantic Parsing with Combinatory Categorial Grammar (CCG)Semantic Parsing with Combinatory Categorial Grammar (CCG)
Semantic Parsing with Combinatory Categorial Grammar (CCG)shakimov
 
Igh maa-2015 nov
Igh maa-2015 novIgh maa-2015 nov
Igh maa-2015 novZach Zhang
 
La tex basics
La tex basicsLa tex basics
La tex basicsawverret
 
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...Future features for openCypher: Schema, Constraints, Subqueries, Configurable...
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...openCypher
 
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012taxonbytes
 
Alternate Parameterizations
Alternate ParameterizationsAlternate Parameterizations
Alternate Parameterizationscseiitgn
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdfHiroshi Ono
 

Similar to Automatic Mathematical Information Retrieval to Perform Translations up to Computer Algebra Systems (20)

NoSQL in Perspective
NoSQL in PerspectiveNoSQL in Perspective
NoSQL in Perspective
 
Incremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesIncremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher Queries
 
Incremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher QueriesIncremental View Maintenance for openCypher Queries
Incremental View Maintenance for openCypher Queries
 
Uncovering Performance Problems in Java Applications with Reference Propagati...
Uncovering Performance Problems in Java Applications with Reference Propagati...Uncovering Performance Problems in Java Applications with Reference Propagati...
Uncovering Performance Problems in Java Applications with Reference Propagati...
 
Parallel Datalog Reasoning in RDFox Presentation
Parallel Datalog Reasoning in RDFox PresentationParallel Datalog Reasoning in RDFox Presentation
Parallel Datalog Reasoning in RDFox Presentation
 
Regular expressions
Regular expressionsRegular expressions
Regular expressions
 
A Distributed Tableau Algorithm for Package-based Description Logics
A Distributed Tableau Algorithm for Package-based Description LogicsA Distributed Tableau Algorithm for Package-based Description Logics
A Distributed Tableau Algorithm for Package-based Description Logics
 
Mathematical Modeling With Maple
Mathematical Modeling With MapleMathematical Modeling With Maple
Mathematical Modeling With Maple
 
Scala as a Declarative Language
Scala as a Declarative LanguageScala as a Declarative Language
Scala as a Declarative Language
 
Project
ProjectProject
Project
 
Semantic Parsing with Combinatory Categorial Grammar (CCG)
Semantic Parsing with Combinatory Categorial Grammar (CCG)Semantic Parsing with Combinatory Categorial Grammar (CCG)
Semantic Parsing with Combinatory Categorial Grammar (CCG)
 
Igh maa-2015 nov
Igh maa-2015 novIgh maa-2015 nov
Igh maa-2015 nov
 
La tex basics
La tex basicsLa tex basics
La tex basics
 
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...Future features for openCypher: Schema, Constraints, Subqueries, Configurable...
Future features for openCypher: Schema, Constraints, Subqueries, Configurable...
 
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012
Franz et. al. 2012. Reconciling Succeeding Classifications, ESA 2012
 
Alternate Parameterizations
Alternate ParameterizationsAlternate Parameterizations
Alternate Parameterizations
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 
scalaliftoff2009.pdf
scalaliftoff2009.pdfscalaliftoff2009.pdf
scalaliftoff2009.pdf
 

More from Scientific Information Analytics Group, Prof. Gipp

More from Scientific Information Analytics Group, Prof. Gipp (11)

A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-...
A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-...A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-...
A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-...
 
A First Step Towards Content Protecting Plagiarism Detection
A First Step Towards Content Protecting Plagiarism Detection  A First Step Towards Content Protecting Plagiarism Detection
A First Step Towards Content Protecting Plagiarism Detection
 
Classification and Clustering of arXiv Documents, Sections, and Abstracts, Co...
Classification and Clustering of arXiv Documents, Sections, and Abstracts, Co...Classification and Clustering of arXiv Documents, Sections, and Abstracts, Co...
Classification and Clustering of arXiv Documents, Sections, and Abstracts, Co...
 
Towards Formula Concept Discovery and Recognition
Towards Formula Concept Discovery and RecognitionTowards Formula Concept Discovery and Recognition
Towards Formula Concept Discovery and Recognition
 
Too Late to Collaborate: Challenges to the Discovery of in-progress Research
Too Late to Collaborate:Challenges tothe Discovery ofin-progress ResearchToo Late to Collaborate:Challenges tothe Discovery ofin-progress Research
Too Late to Collaborate: Challenges to the Discovery of in-progress Research
 
Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathe...
Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathe...Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathe...
Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathe...
 
Repurposing Open Source Tools for Open Science: a Practical Guide
Repurposing Open Source Tools for Open Science: a Practical GuideRepurposing Open Source Tools for Open Science: a Practical Guide
Repurposing Open Source Tools for Open Science: a Practical Guide
 
Blockchain based Trusted Timestamping for Research Data and Preprints using O...
Blockchain based Trusted Timestamping for Research Data and Preprints using O...Blockchain based Trusted Timestamping for Research Data and Preprints using O...
Blockchain based Trusted Timestamping for Research Data and Preprints using O...
 
Analyzing Nontextual Content Features to Detect Academic Plagiarism
Analyzing Nontextual Content Features to Detect Academic PlagiarismAnalyzing Nontextual Content Features to Detect Academic Plagiarism
Analyzing Nontextual Content Features to Detect Academic Plagiarism
 
A Semantically Enriched Recommendation & Visualization Approach for Academic ...
A Semantically Enriched Recommendation & Visualization Approach for Academic ...A Semantically Enriched Recommendation & Visualization Approach for Academic ...
A Semantically Enriched Recommendation & Visualization Approach for Academic ...
 
An Adaptive Image-based Plagiarism Detection Approach
An Adaptive Image-based Plagiarism Detection ApproachAn Adaptive Image-based Plagiarism Detection Approach
An Adaptive Image-based Plagiarism Detection Approach
 

Recently uploaded

Ukraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSUkraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSAishani27
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionfulawalesam
 
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiLow Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiSuhani Kapoor
 
Unveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystUnveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystSamantha Rae Coolbeth
 
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip CallDelhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Callshivangimorya083
 
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptxEMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptxthyngster
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAroojKhan71
 
04242024_CCC TUG_Joins and Relationships
04242024_CCC TUG_Joins and Relationships04242024_CCC TUG_Joins and Relationships
04242024_CCC TUG_Joins and Relationshipsccctableauusergroup
 
B2 Creative Industry Response Evaluation.docx
B2 Creative Industry Response Evaluation.docxB2 Creative Industry Response Evaluation.docx
B2 Creative Industry Response Evaluation.docxStephen266013
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfMarinCaroMartnezBerg
 
Smarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxSmarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxolyaivanovalion
 
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Callshivangimorya083
 
Log Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxLog Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxJohnnyPlasten
 
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptdokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptSonatrach
 
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdf
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdfMarket Analysis in the 5 Largest Economic Countries in Southeast Asia.pdf
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdfRachmat Ramadhan H
 
Brighton SEO | April 2024 | Data Storytelling
Brighton SEO | April 2024 | Data StorytellingBrighton SEO | April 2024 | Data Storytelling
Brighton SEO | April 2024 | Data StorytellingNeil Barnes
 
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Serviceranjana rawat
 
Halmar dropshipping via API with DroFx
Halmar  dropshipping  via API with DroFxHalmar  dropshipping  via API with DroFx
Halmar dropshipping via API with DroFxolyaivanovalion
 

Recently uploaded (20)

Ukraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICSUkraine War presentation: KNOW THE BASICS
Ukraine War presentation: KNOW THE BASICS
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interaction
 
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service BhilaiLow Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
Low Rate Call Girls Bhilai Anika 8250192130 Independent Escort Service Bhilai
 
Unveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data AnalystUnveiling Insights: The Role of a Data Analyst
Unveiling Insights: The Role of a Data Analyst
 
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip CallDelhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
 
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptxEMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM  TRACKING WITH GOOGLE ANALYTICS.pptx
EMERCE - 2024 - AMSTERDAM - CROSS-PLATFORM TRACKING WITH GOOGLE ANALYTICS.pptx
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
 
꧁❤ Aerocity Call Girls Service Aerocity Delhi ❤꧂ 9999965857 ☎️ Hard And Sexy ...
꧁❤ Aerocity Call Girls Service Aerocity Delhi ❤꧂ 9999965857 ☎️ Hard And Sexy ...꧁❤ Aerocity Call Girls Service Aerocity Delhi ❤꧂ 9999965857 ☎️ Hard And Sexy ...
꧁❤ Aerocity Call Girls Service Aerocity Delhi ❤꧂ 9999965857 ☎️ Hard And Sexy ...
 
04242024_CCC TUG_Joins and Relationships
04242024_CCC TUG_Joins and Relationships04242024_CCC TUG_Joins and Relationships
04242024_CCC TUG_Joins and Relationships
 
B2 Creative Industry Response Evaluation.docx
B2 Creative Industry Response Evaluation.docxB2 Creative Industry Response Evaluation.docx
B2 Creative Industry Response Evaluation.docx
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdf
 
Smarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptxSmarteg dropshipping via API with DroFx.pptx
Smarteg dropshipping via API with DroFx.pptx
 
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call
꧁❤ Greater Noida Call Girls Delhi ❤꧂ 9711199171 ☎️ Hard And Sexy Vip Call
 
Log Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxLog Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptx
 
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.pptdokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
dokumen.tips_chapter-4-transient-heat-conduction-mehmet-kanoglu.ppt
 
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdf
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdfMarket Analysis in the 5 Largest Economic Countries in Southeast Asia.pdf
Market Analysis in the 5 Largest Economic Countries in Southeast Asia.pdf
 
Brighton SEO | April 2024 | Data Storytelling
Brighton SEO | April 2024 | Data StorytellingBrighton SEO | April 2024 | Data Storytelling
Brighton SEO | April 2024 | Data Storytelling
 
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service
(PARI) Call Girls Wanowrie ( 7001035870 ) HI-Fi Pune Escorts Service
 
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in Kishangarh
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in  KishangarhDelhi 99530 vip 56974 Genuine Escort Service Call Girls in  Kishangarh
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in Kishangarh
 
Halmar dropshipping via API with DroFx
Halmar  dropshipping  via API with DroFxHalmar  dropshipping  via API with DroFx
Halmar dropshipping via API with DroFx
 

Automatic Mathematical Information Retrieval to Perform Translations up to Computer Algebra Systems

  • 1. Automatic Mathematical Information Retrieval to Perform Translations up to Computer Algebra Systems André Greiner-Petter* June 6, 2018 University of Konstanz Germany *sponsored by SIGIR Student Travel Grant @GreinerPetter 1/9
  • 3. Motivation - Formulae Presentations DLMF 18.3 A Jacobi polynomial in different systems. Rendered Version: P (α,β) n (cos(aΘ)) Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n,alpha,beta,cos(a*Theta)) CAS Mathematica: JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]] 2/9
  • 4. Motivation - Formulae Presentations DLMF 18.3 A Jacobi polynomial in different systems. Rendered Version: P (α,β) n (cos(aΘ)) Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n,alpha,beta,cos(a*Theta)) CAS Mathematica: JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]] 2/9
  • 5. Motivation - Formulae Presentations DLMF 18.3 A Jacobi polynomial in different systems. Rendered Version: P (α,β) n (cos(aΘ)) Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n,alpha,beta,cos(a*Theta)) CAS Mathematica: JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]] 2/9
  • 6. Motivation - Formulae Presentations DLMF 18.3 A Jacobi polynomial in different systems. Rendered Version: P (α,β) n (cos(aΘ)) Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n,alpha,beta,cos(a*Theta)) CAS Mathematica: JacobiP[n,[Alpha],[Beta],Cos[a [CapitalTheta]]] 2/9
  • 7. Presentation To Computation with semantic information
  • 8. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n, alpha, beta, cos(a*Theta)) Potential Problems: • Differences in syntax • Function is not implemented in one system, • Function has multiple representations in one system, • Differences in definitions. 3/9
  • 9. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n, alpha, beta, cos(a*Theta)) Potential Problems: • Differences in syntax • Function is not implemented in one system, • Function has multiple representations in one system, • Differences in definitions. 3/9
  • 10. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP($2, $0, $1, $3) Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, • Function has multiple representations in one system, • Differences in definitions. 3/9
  • 11. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n, alpha, beta, cos(a*Theta)) Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, • Function has multiple representations in one system, • Differences in definitions. 3/9
  • 12. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: DLMF 18.5.7 Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, translate equivalent presentations • Function has multiple representations in one system, • Differences in definitions. n =0 (n + α + β + 1) (α + + 1)n− ! (n − )! x − 1 2 3/9
  • 13. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP or Jacobi or JacobiPoly Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, translate equivalent presentations • Function has multiple representations in one system, • Differences in definitions. 3/9
  • 14. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP or Jacobi or JacobiPoly Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, translate equivalent presentations • Function has multiple representations in one system, just pick a valid translation • Differences in definitions. 3/9
  • 15. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n, alpha, beta, cos(a*Theta)) Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, translate equivalent presentations • Function has multiple representations in one system, just pick a valid translation • Differences in definitions. 3/9
  • 16. Problems of Translations DLMF 18.3 Semantic LATEX: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} CAS Maple: JacobiP(n, alpha, beta, cos(a*Theta)) Potential Problems: • Differences in syntax ← solved by translation patterns • Function is not implemented in one system, translate equivalent presentations • Function has multiple representations in one system, just pick a valid translation • Differences in definitions. ← wait... What? 3/9
  • 17. Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions Rendered Version Semantic LATEX CAS Maple arccot(z) acot@{z} arccot(z) 4/9
  • 18. Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions Rendered Version Semantic LATEX CAS Maple arccot(z) acot@{z} arccot(z) Maple Figure 1: (arccot(z)) with branch cut at [−∞i, −i], [i, ∞i]. DLMF & Mathematica Figure 2: (arccot(z)) with branch cut at [−i, i]. 4/9
  • 19. Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions Rendered Version Semantic LATEX CAS Maple arccot(z) acot@{z} arccot(z) Maple Figure 1: (arccot(z)) with branch cut at [−∞i, −i], [i, ∞i]. DLMF & Mathematica Figure 2: (arccot(z)) with branch cut at [−i, i]. 4/9
  • 20. Problems of Translations DLMF 4.23.9 Maple Inv. Trig. Functions Rendered Version Semantic LATEX CAS Maple arccot(z) acot@{z} arctan(1/z) Maple Figure 1: (arccot(z)) with branch cut at [−∞i, −i], [i, ∞i]. DLMF & Mathematica Figure 2: (arccot(z)) with branch cut at [−i, i]. 4/9
  • 21. Presentation To Computation (P2C) without semantic information
  • 22. Problems of Generic LATEX DLMF 18.3 Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantics: JacobiP{alpha}{beta}{n}@{cos@{aTheta}} Potential Problems: • Is P a function, variable, constant? • Is cos(aΘ) an argument of P or part of a multiplication? • What are α, β, n, a, and Θ? 5/9
  • 23. Problems of Generic LATEX DLMF 18.3 Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantics: Jacobi polynomial or Legendre function or Ferrers function or ... Potential Problems: • Is P a function, variable, constant? • Is cos(aΘ) an argument of P or part of a multiplication? • What are α, β, n, a, and Θ? 5/9
  • 24. Problems of Generic LATEX DLMF 18.3 Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantics: P(cos(aΘ)) vs P · (cos(aΘ)) Potential Problems: • Is P a function, variable, constant? • Is cos(aΘ) an argument of P or part of a multiplication? • What are α, β, n, a, and Θ? 5/9
  • 25. Problems of Generic LATEX DLMF 18.3 Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Semantics: Variable or 2nd Feigenbaum constant or ... Potential Problems: • Is P a function, variable, constant? • Is cos(aΘ) an argument of P or part of a multiplication? • What are α, β, n, a, and Θ? 5/9
  • 27. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 28. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 29. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 30. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 31. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 32. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 33. Multiple-Scan Approach Rendered LATEX: P (α,β) n (cos(aΘ)) The Naive Approach How does a reader understands the mathematical formula? • he knows the symbols and structure, knowledge-based pattern recognition • it was previously introduced in the paper (e.g. in definitions, the text or in other referenced publications), analyse the context from near to far • he searching the formula in books or online dictionary-based pattern recognition 6/9
  • 34. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 35. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 36. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 37. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 38. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 39. Multiple-Scan Approach Generic LATEX: P_n^{(alpha,beta)}(cos(aTheta)) Adopt Human Behavior Let’s try to adopt the previous steps • pattern recognition narrow down possible meanings from the structure of the expression • context analysis Near-Field-Analysis (NFA), e.g., extract identifier-definien pairs from text, analyze definition environments, ... Far-Field-Analysis (FFA), e.g., overall topic of the paper, citations, author’s field of interest, ... 7/9
  • 40. Multiple-Scan Approach Expression Analysis • 1 subscript • 2 supscripts in parentheses • 1 variable • The variable is a subexpression Expression Analysis • 1 subscript • 2 supscripts in parentheses • 1 variable • The variable is a subexpression CONCLUSION JacobiP{alpha}{beta}{n}@{cos@{aTheta}} Semantic LaTeX JacobiP{alpha}{beta}{n}@{cos@{aTheta}} Semantic LaTeX MLPMLP MLP Syntax TreeMLP Syntax TreeMLP Syntax Tree P_n^{(alpha, beta)}(cos(aTheta)) Generic LaTeX P_n^{(alpha, beta)}(cos(aTheta)) Generic LaTeX Near-Field-Analysis Multiple scans of expression and its environment Far-Field-Analysis 8/9
  • 41. Wikipedia Recommender System A real-time recommender system for semantic version of mathematical input included in the editor of Wikipedia articles. • real-time recommendations • ordered from most likely to impossible • consider the context 9/9
  • 42. Thank you for your attention!