OntoMаthPro Ontology: A Linked Data Hub for MathematicsAlik Kirillovich
O. Nevzorova, N. Zhiltsov, A. Kirillovich, E. Lipachev. OntoMathPro Ontology: A Linked Data Hub for Mathematics // Knowledge Engineering and the Semantic Web. 5th International Conference, Proceedings. — Communications in Computer and Information Science, Vol. 468 — Springer International Publishing — 2014 — pp. 105-119.
The Linked Open Data (LOD) cloud contains tremendous amounts of interlinked instances, from where we can retrieve abundant knowledge. However, because of the heterogeneous and big ontologies, it is time consuming to learn all the ontologies manually and it is difficult to observe which properties are important for describing instances of a specific class. In order to construct an ontology that can help users easily access to various data sets, we propose a semi-automatic ontology inte- gration framework that can reduce the heterogeneity of ontologies and retrieve frequently used core properties for each class. The framework consists of three main components: graph-based ontology integration, machine-learning-based ontology schema extraction, and an ontology merger. By analyzing the instances of the linked data sets, this framework acquires ontological knowledge and constructs a high-quality integrated ontology, which is easily understandable and effective in knowledge ac- quisition from various data sets using simple SPARQL queries.
OntoMаthPro Ontology: A Linked Data Hub for MathematicsAlik Kirillovich
O. Nevzorova, N. Zhiltsov, A. Kirillovich, E. Lipachev. OntoMathPro Ontology: A Linked Data Hub for Mathematics // Knowledge Engineering and the Semantic Web. 5th International Conference, Proceedings. — Communications in Computer and Information Science, Vol. 468 — Springer International Publishing — 2014 — pp. 105-119.
The Linked Open Data (LOD) cloud contains tremendous amounts of interlinked instances, from where we can retrieve abundant knowledge. However, because of the heterogeneous and big ontologies, it is time consuming to learn all the ontologies manually and it is difficult to observe which properties are important for describing instances of a specific class. In order to construct an ontology that can help users easily access to various data sets, we propose a semi-automatic ontology inte- gration framework that can reduce the heterogeneity of ontologies and retrieve frequently used core properties for each class. The framework consists of three main components: graph-based ontology integration, machine-learning-based ontology schema extraction, and an ontology merger. By analyzing the instances of the linked data sets, this framework acquires ontological knowledge and constructs a high-quality integrated ontology, which is easily understandable and effective in knowledge ac- quisition from various data sets using simple SPARQL queries.
I. JOURNAL OF MODERN SCIENCE AND ARTS
An international Journal concerned with publishing in all scientific and literary fields
Papers Published in Arabic and English
A hierarchical approach for semi structured document indexing andIbrahim Bounhas
I. Bounhas and Y. Slimani. A hierarchical approach for semi-structured document indexing and terminology extraction. International Conference on Information Retrieval and Knowledge Management (CAMP’2010), Shah-Alam, Malaysia, March 16 – 18, 2010, pp. 314-319.
Ontology learning techniques and applications computer science thesis writing...Tutors India
At Tutors India, we offer Computer science and Information Technology Research Guidance services – We deliver exceptional work where your dissertation will deserve publication without significant reworking or alternation.
For #Enquiry
https://www.tutorsindia.com
info@tutorsindia.com
(Whatsapp): +91-8754446690
(UK): +44-1143520021
The Computer Science Ontology: A Large-Scale Taxonomy of Research AreasAngelo Salatino
Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 15K topics and 70K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data.
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
The Computer Science Ontology: A Large-Scale Taxonomy of Research AreasAngelo Salatino
Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 15K topics and 70K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data.
Invited Talk: Early Detection of Research Topics Angelo Salatino
Slides of my talk at Chan Zuckerberg Initiative (Meta)
Abstract:
The ability to promptly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. While the literature describes several approaches which aim to identify the emergence of new research topics early in their lifecycle, these rely on the assumption that the topic in question is already associated with a number of publications and consistently referred to by a community of researchers. Hence, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. In this paper, we begin to address this challenge by performing a study of the dynamics preceding the creation of new topics. This study indicates that the emergence of a new topic is anticipated by a significant increase in the pace of collaboration between relevant research areas, which can be seen as the ‘parents’ of the new topic. These initial findings (i) confirm our hypothesis that it is possible in principle to detect the emergence of a new topic at the embryonic stage, (ii) provide new empirical evidence supporting relevant theories in Philosophy of Science, and also (iii) suggest that new topics tend to emerge in an environment in which weakly interconnected research areas begin to cross-fertilise.
HyperMembrane Structures for Open Source Cognitive ComputingJack Park
Open source "cognitive computing" systems, specifically OpenSherlock; describes a HyperMembrane structure, a kind of information fabric, for machine reading, literature-based discovery, deep question answering. Platform is open source, uses ElasticSearch, topic maps, JSON, link-grammar parsing, and qualitative process models.
I. JOURNAL OF MODERN SCIENCE AND ARTS
An international Journal concerned with publishing in all scientific and literary fields
Papers Published in Arabic and English
A hierarchical approach for semi structured document indexing andIbrahim Bounhas
I. Bounhas and Y. Slimani. A hierarchical approach for semi-structured document indexing and terminology extraction. International Conference on Information Retrieval and Knowledge Management (CAMP’2010), Shah-Alam, Malaysia, March 16 – 18, 2010, pp. 314-319.
Ontology learning techniques and applications computer science thesis writing...Tutors India
At Tutors India, we offer Computer science and Information Technology Research Guidance services – We deliver exceptional work where your dissertation will deserve publication without significant reworking or alternation.
For #Enquiry
https://www.tutorsindia.com
info@tutorsindia.com
(Whatsapp): +91-8754446690
(UK): +44-1143520021
The Computer Science Ontology: A Large-Scale Taxonomy of Research AreasAngelo Salatino
Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 15K topics and 70K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data.
Applying machine learning techniques to big data in the scholarly domainAngelo Salatino
Slides of the Lecture at the 5th International School on Applied Probability Theory,Communications Technologies & Data Science (APTCT-2020)
12 Nov 2020
The Computer Science Ontology: A Large-Scale Taxonomy of Research AreasAngelo Salatino
Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 15K topics and 70K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data.
Invited Talk: Early Detection of Research Topics Angelo Salatino
Slides of my talk at Chan Zuckerberg Initiative (Meta)
Abstract:
The ability to promptly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. While the literature describes several approaches which aim to identify the emergence of new research topics early in their lifecycle, these rely on the assumption that the topic in question is already associated with a number of publications and consistently referred to by a community of researchers. Hence, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. In this paper, we begin to address this challenge by performing a study of the dynamics preceding the creation of new topics. This study indicates that the emergence of a new topic is anticipated by a significant increase in the pace of collaboration between relevant research areas, which can be seen as the ‘parents’ of the new topic. These initial findings (i) confirm our hypothesis that it is possible in principle to detect the emergence of a new topic at the embryonic stage, (ii) provide new empirical evidence supporting relevant theories in Philosophy of Science, and also (iii) suggest that new topics tend to emerge in an environment in which weakly interconnected research areas begin to cross-fertilise.
HyperMembrane Structures for Open Source Cognitive ComputingJack Park
Open source "cognitive computing" systems, specifically OpenSherlock; describes a HyperMembrane structure, a kind of information fabric, for machine reading, literature-based discovery, deep question answering. Platform is open source, uses ElasticSearch, topic maps, JSON, link-grammar parsing, and qualitative process models.
Between information retrieval services and bibliometrics research. New ...Andrea Scharnhorst
R. Koopman, S. Wang, A. Scharnhorst (2015) Between information retrieval services and bibliometrics research. New ways of semantic browsing and visual analytics. Presentation at the Sigmetrics workshop, ASIST 2015, November 7, 2015 St. Louis, Missouri
This webinar will explain what text-mining is and why it is important to text-mine research papers. We will consider real-world use-cases and applications and discuss barriers to wider adoption of text-mining.
We will also provide practical advice on how to start text-mining research papers, such as where to obtain data, how to access relevant APIs and highlight some of the tools that are available.
We made a system to predict which scientific topics will become important in the future. To predict the future of science, we have used Machine Learning algorithms to learn how science behaved in the past and to use the resulting model to predict future trends in science.
#scichallenge2017
Automatic Classification of Springer Nature Proceedings with Smart Topic MinerFrancesco Osborne
The process of classifying scholarly outputs is crucial to ensure timely access to knowledge. However, this process is typically carried out manually by expert editors, leading to high costs and slow throughput. In this paper we present Smart Topic Miner (STM), a novel solution which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses in real time a set of publications provided by an editor and produces a structured set of topics and a number of Springer Nature classification tags, which best characterise the given input. In this paper we present the architecture of the system and report on an evaluation study conducted with a team of Springer Nature editors. The results of the evaluation, which showed that STM classifies publications with a high degree of accuracy, are very encouraging and as a result we are currently discussing the required next steps to ensure large-scale deployment within the company.
Why I am Not a Philosopher (October 2006)Barry Smith
Forms part of a training course in ontology given in Buffalo in 2009. For details and accompanying video see http://ontology.buffalo.edu/smith/IntroOntology_Course.html
Authors: Pavel Brazdil, Jan N. van Rijn, Carlos Soares, Joaquin Vanschoren
Provide a comprehensive and systematic overview of metalearning
Blends theory and practice, presenting state-of-the-art methodologies
An update edition on the successful first edition https://link.springer.com/book/10.1007/978-3-540-73263-1
This book is open access, which means that you have free and unlimited access
Ukrainian Catholic University
Faculty of Applied Sciences
Data Science Master Program
January 21st
Abstract. Novelty is an inherent part of innovations and discoveries. Such processes may be considered as the appearance of new ideas or as the emergence of atypical connections between existing ones. The importance of such connections hints for investigation of innovations through network or graph representation in the space of ideas. In such representation, a graph node corresponds to the relevant notion (idea), whereas an edge between two nodes means that the corresponding notions have been used in a common context. The question addressed in this research is the possibility to identify the edges between existing concepts where the innovations may emerge. To this end, a well-documented scientific knowledge landscape has been used. Namely, we downloaded 1.2M arXiv.org manuscripts dated starting from April 2007 and until September 2019; and extracted relevant concepts for them using ScienceWISE.info platform. Combining approaches developed in complex networks science and graph embedding the predictability of edges (links) on the scientific knowledge landscape where the innovations may appear is investigated. We argue that the conclusions drawn from this analysis may be used not only to the scientific knowledge analysis but are rather generic and may be applied to any domain that involves creativity within.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
5. World Digital Mathematical Library (WDML)
WDML: mathematical concepts, objects and logical relationships
Direct access to the objects of mathematical knowledge
6. International Mathematics Union
World Digital Mathematical Library
working group
Workshop 2012
(Washington)
Workshop 2014
(Seoul)
Workshop 2016
(Toronto)
Local working groups: Wolfram Research, Kazan, ….
7. Outline
1. World Digital Mathematical Library
2. OntoMath Digital Ecosystem
3. Semantic publishing platform
4. Ontologies
1. Mocassin ontology
2. OntoMathPro ontology
5. Applications
1. Semantic search for mathematical formulas
2. Recommender system
6. Publications
8. OntoMath ecosystem
OntoMath is an ecosystem of ontologies, text analytics tools, and applications
for math knowledge management
9. Outline
1. World Digital Mathematical Library
2. OntoMath Digital Ecosystem
3. Semantic publishing platform
4. Ontologies
1. Mocassin ontology
2. OntoMathPro ontology
5. Applications
1. Semantic search for mathematical formulas
2. Recommender system
6. Publications
10. OntoMath ecosystem
OntoMath is an ecosystem of ontologies, text analytics tools, and applications
for math knowledge management
The core component of the OntoMath digital ecosystem is a Semantic publishing platform
11. Semantic publishing platform (1)
Semantic publishing platform analyzes the underlying semantics in mathematical
scholarly papers and builds their consolidated ontology-based representation
Input: Output:
Collection of math
articles in
Linking Open Data
representation
15. AKT Portal ontology
• Journal
• Author
• Publication-Reference
• …
Matadata extraction
Author: V.I. Arnold
Title: On the matricial version…
Journal: Japan. J. Math. 1, 2006
Affiliation: Steklov Math. Institute
Content:
The congruences modulo the
primary numbers n = pa are
studied for the traces of the
matrices An and An−ϕ(n) , where
A is an integer matrix and ϕ(n)
is the number of residues
modulo …
16. AKT Portal ontology
• Journal
• Author
• Publication-Reference
• …
Matadata extraction
Author: V.I. Arnold
Title: On the matricial version…
Journal: Japan. J. Math. 1, 2006
Affiliation: Steklov Math. Institute
Content:
The congruences modulo the
primary numbers n = pa are
studied for the traces of the
matrices An and An−ϕ(n) , where
A is an integer matrix and ϕ(n)
is the number of residues
modulo …
19. The congruences modulo the primary numbers n
= pa are studied for the traces of the matrices An
and An−ϕ(n) , where A is an integer matrix and
ϕ(n) is the number of residues n, relatively prime
to n.
We present an algorithm to decide whether
these congruences hold for all the integer
matrices A, when the prime number p is fixed.
The algorithm is explicitly applied for many
values of p, …
Ontology-based Terminology Extraction
OntoMathPro ontology
20. Formulas binding
for all integer matrices A, primes p, and natural numbers n. For (1×1)-matrices,
these are just the usual Euler congruences …
21. Outline
1. World Digital Mathematical Library
2. OntoMath Digital Ecosystem
3. Semantic publishing platform
4. Ontologies
1. Mocassin ontology
2. OntoMathPro ontology
5. Applications
1. Semantic search for mathematical formulas
2. Recommender system
6. Publications
22. Mocassin
Mocassin is an ontology of elements of the logical structure of mathematical papers
25. OntoMаthPro (2)
Concepts:
• Taxonomies:
Fields of mathematics
Mathematical objects
• Concept description:
English and Russian labels
Definitions,
Relations with other concepts
Links to external terminologies (DBpedia and ScienceWISE)
• Total: 3450 concepts
Logics, Set theory, Geometry, Differential Geometry, …
Set, Function, Integral, Lambda matrix, Christoffel Symbol, …
26. OntoMаthPro (3)
Relations:
• Taxonomic relation (ISA)
• Belongingness of objects to fields of mathematics
• Logical dependency
• Associative relation between objects
• Associative relation between problems and methods
Lambda matrix is a Matrix
Barycentric Coordinates belongs to Metric Geometry
Christoffel Symbol is defined by Connectedness
Chebyshev Iterative Method see also Numerical Solution of Linear Equation Systems
Matric algebraic linear equation is solved by Gauss method
27. Outline
1. World Digital Mathematical Library
2. OntoMath Digital Ecosystem
3. Semantic publishing platform
4. Ontologies
1. Mocassin ontology
2. OntoMathPro ontology
5. Applications
1. Semantic search for mathematical formulas
2. Recommender system
6. Publications
28. OntoMath ecosystem
OntoMath is an ecosystem of ontologies, text analytics tools, and applications
for math knowledge management
29. • There are currently many math formula search engines out
there
• but they are mostly syntactical, and allow only simple search
by expression patterns
• Our approach is semantic, and, therefore, can find formulas
with respect to a given math concept
• Online demo: http://lobachevskii-dml/mathsearch/
(uni)quation, Springer LaTeX Search, Wikipedia Formula Search, Wolfram Formula Search…
Find formulas, containing “(a + b)2”.
Find formulas that contain variables, expressing angles.
Semantic search for mathematical formulas
30. The user enters keywords, filtering suggestions of the system
31. First column contains a variable standing for the query concept in the relevant formula
43. Outline
1. World Digital Mathematical Library
2. OntoMath Digital Ecosystem
3. Semantic publishing platform
4. Ontologies
1. Mocassin ontology
2. OntoMathPro ontology
5. Applications
1. Semantic search for mathematical formulas
2. Recommender system
6. Publications
44. Main publications
• Alexander Elizarov, Alexander Kirillovich, Evgeny Lipachev, Olga Nevzorova. Digital Ecosystem
OntoMath: Mathematical Knowledge Analytics and Management // Kalinichenko L., Kuznetsov S.,
Manolopoulos Y. (eds). XVIII International Conference on Data Analytics and Management in Data
Intensive Domains (DAMDID/RCDL 2016). Communications in Computer and Information Science,
vol 706. Springer, Cham, 2017. Pp. 33-46
• Olga Nevzorova, Nikita Zhiltsov, Alexander Kirillovich, Evgeny Lipachev. OntoMathPRO Ontology: A
Linked Data Hub for Mathematics // Pavel Klinov, Dmitry Mouromstev (eds.) Proceedings of the 5th
International Conference on Knowledge Engineering and Semantic Web (KESW 2014).
Communications in Computer and Information Science, vol. 468. Springer, Cham, 2014. Pp. 105–
119
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