Cooperating Techniques for Extracting Conceptual Taxonomies from TextFulvio Rotella
The current abundance of electronic documents requires automatic techniques that support the users in understanding their content and extracting useful information. To this aim, it is important to have conceptual taxonomies that express common sense and implicit relationships among concepts. This work proposes a mix of several tech niques that are brought to cooperation for learning them automatically. Although the work is at a preliminary stage, interesting initial results suggest to go on extending and improving the approach.
More details can be found here:
http://www.di.uniba.it/~loglisci/MCP2011/mce2011.pdf
Analogy is one of the most studied representatives of a family of non-classical forms of reasoning working across different domains, usually taken to play a crucial role in creative thought and problem-solving. In the first part of the talk, I will shortly introduce general principles of computational analogy models (relying on a generalization-based approach to analogy-making). We will then have a closer look at Heuristic-Driven Theory Projection (HDTP) as an example for a theoretical framework and implemented system: HDTP computes analogical relations and inferences for domains which are represented using many-sorted first-order logic languages, applying a restricted form of higher-order anti-unification for finding shared structural elements common to both domains. The presentation of the framework will be followed by a few reflections on the "cognitive plausibility" of the approach motivated by theoretical complexity and tractability considerations.
In the second part of the talk I will discuss an application of HDTP to modeling essential parts of concept blending processes as current "hot topic" in Cognitive Science. Here, I will sketch an analogy-inspired formal account of concept blending —developed in the European FP7-funded Concept Invention Theory (COINVENT) project— combining HDTP with mechanisms from Case-Based Reasoning.
Cooperating Techniques for Extracting Conceptual Taxonomies from TextFulvio Rotella
The current abundance of electronic documents requires automatic techniques that support the users in understanding their content and extracting useful information. To this aim, it is important to have conceptual taxonomies that express common sense and implicit relationships among concepts. This work proposes a mix of several tech niques that are brought to cooperation for learning them automatically. Although the work is at a preliminary stage, interesting initial results suggest to go on extending and improving the approach.
More details can be found here:
http://www.di.uniba.it/~loglisci/MCP2011/mce2011.pdf
Analogy is one of the most studied representatives of a family of non-classical forms of reasoning working across different domains, usually taken to play a crucial role in creative thought and problem-solving. In the first part of the talk, I will shortly introduce general principles of computational analogy models (relying on a generalization-based approach to analogy-making). We will then have a closer look at Heuristic-Driven Theory Projection (HDTP) as an example for a theoretical framework and implemented system: HDTP computes analogical relations and inferences for domains which are represented using many-sorted first-order logic languages, applying a restricted form of higher-order anti-unification for finding shared structural elements common to both domains. The presentation of the framework will be followed by a few reflections on the "cognitive plausibility" of the approach motivated by theoretical complexity and tractability considerations.
In the second part of the talk I will discuss an application of HDTP to modeling essential parts of concept blending processes as current "hot topic" in Cognitive Science. Here, I will sketch an analogy-inspired formal account of concept blending —developed in the European FP7-funded Concept Invention Theory (COINVENT) project— combining HDTP with mechanisms from Case-Based Reasoning.
ConNeKTion: A Tool for Exploiting Conceptual Graphs Automatically Learned fro...University of Bari (Italy)
Studying, understanding and exploiting the content of a digital library, and extracting useful information thereof, require automatic techniques that can effectively support the users. To this aim, a relevant role can be played by concept taxonomies. Unfortunately, the availability of such a kind of resources is limited, and their manual building and maintenance are costly and error-prone. This work presents ConNeKTion, a tool for conceptual graph learning and exploitation. It allows to learn conceptual graphs from plain text and to enrich them by finding concept generalizations. The resulting graph can be used for several purposes: finding relationships between concepts (if any), filtering the concepts from a particular perspective, keyword extraction and information retrieval. A suitable control panel is provided for the user to comfortably carry out these activities.
2007. Introduction to the panel 'Pragmatic Interfaces' organised by the authors at the International Pragmatics Conference (IPRA) in Goteborg (Sweden), July 2007. Didier Maillat and Louis de Saussure
The spread and abundance of electronic documents requires automatic techniques for extracting useful information from the text they contain. The availability of conceptual taxonomies can be of great help, but manually building them is a complex and costly task. Building on previous work, we propose a technique to automatically extract conceptual graphs from text and reason with them. Since automated learning of taxonomies needs to be robust with respect to missing or partial knowledge and flexible with respect to noise, this work proposes a way to deal with these problems. The case of poor data/sparse concepts is tackled by finding generalizations among disjoint pieces of knowledge. Noise is
handled by introducing soft relationships among concepts rather than hard ones, and applying a probabilistic inferential setting. In particular, we propose to reason on the extracted graph using different kinds of relationships among concepts, where each arc/relationship is associated to a number that represents its likelihood among all possible worlds, and to face the problem of sparse knowledge by using generalizations among distant concepts as bridges between disjoint portions of knowledge.
ConNeKTion: A Tool for Exploiting Conceptual Graphs Automatically Learned fro...University of Bari (Italy)
Studying, understanding and exploiting the content of a digital library, and extracting useful information thereof, require automatic techniques that can effectively support the users. To this aim, a relevant role can be played by concept taxonomies. Unfortunately, the availability of such a kind of resources is limited, and their manual building and maintenance are costly and error-prone. This work presents ConNeKTion, a tool for conceptual graph learning and exploitation. It allows to learn conceptual graphs from plain text and to enrich them by finding concept generalizations. The resulting graph can be used for several purposes: finding relationships between concepts (if any), filtering the concepts from a particular perspective, keyword extraction and information retrieval. A suitable control panel is provided for the user to comfortably carry out these activities.
2007. Introduction to the panel 'Pragmatic Interfaces' organised by the authors at the International Pragmatics Conference (IPRA) in Goteborg (Sweden), July 2007. Didier Maillat and Louis de Saussure
The spread and abundance of electronic documents requires automatic techniques for extracting useful information from the text they contain. The availability of conceptual taxonomies can be of great help, but manually building them is a complex and costly task. Building on previous work, we propose a technique to automatically extract conceptual graphs from text and reason with them. Since automated learning of taxonomies needs to be robust with respect to missing or partial knowledge and flexible with respect to noise, this work proposes a way to deal with these problems. The case of poor data/sparse concepts is tackled by finding generalizations among disjoint pieces of knowledge. Noise is
handled by introducing soft relationships among concepts rather than hard ones, and applying a probabilistic inferential setting. In particular, we propose to reason on the extracted graph using different kinds of relationships among concepts, where each arc/relationship is associated to a number that represents its likelihood among all possible worlds, and to face the problem of sparse knowledge by using generalizations among distant concepts as bridges between disjoint portions of knowledge.
Ontologies constitute formal models of some aspect of the
world that may be used for drawing interesting logical conclusions even
for large models. Software models capture relevant characteristics of a
software artifact to be developed, yet, most often these software models
have limited formal semantics, or the underlying (often graphical) software
language varies from case to case in a way that makes it hard if
not impossible to fix its semantics. In this contribution, we survey the
use of ontology technologies for software modeling in order to carry over
advantages from ontology technologies to the software modeling domain.
It will turn out that ontology-based metamodels constitute a core means
for exploiting expressive ontology reasoning in the software modeling domain
while remaining flexible enough to accommodate varying needs of
software modelers.
Cognitive Agents with Commonsense - Invited Talk at Istituto Italiano di Tecn...Antonio Lieto
Cognitive Agents with Commonsense - Invited Talk at Istituto Italiano di Tecnologia (IIT), I-Cog Initiative. https://www.facebook.com/icog.initiative/posts/129265685733532
Different Semantic Perspectives for Question Answering SystemsAndre Freitas
Question Answering systems define one of the most complex tasks in computational semantics. The intrinsic complexity of the QA task allows researchers of QA systems to investigate and explore different perspectives of semantics. However, this complexity also induces a bias towards a systems perspective, where researchers are alienated from a deeper reasoning on the semantic principles that are in place within the different components of the system. In this talk we will explore the semantic challenges, principles and perspectives behind the components of QA systems, aiming at providing a principled map and overview on the contribution of each component within the QA semantic interpretation goal.
The tutorial has been presented at CAISE 2010. The tutorial discusses the state-of-the-art on research addresseing the quality of data at the conceptual level (conceptual schemas) and of Ontologies
Presentation of "Challenges in transfer learning in NLP" from Madrid Natural Language Processing Meetup Event, May, 2019.
https://www.meetup.com/es-ES/Madrid-Natural-Language-Processing-meetup/
Practical related work in repository: https://github.com/laraolmos/madrid-nlp-meetup
Imran Sarwar Bajwa, [2010], "Context Based Meaning Extraction by Means of Markov Logic", in International Journal of Computer Theory and Engineering - (IJCTE) 2(1) pp:35-38, February 2010
Faire Datenökonomie für Wirtschaft, Wissenschaft und Gesellschaft: Was brauch...Christoph Lange
In Wirtschaft und Wissenschaft entstehen zunehmend Infrastrukturen für Datenaustausch. Der Wirtschaft ist Vertrauen unter Geschäftspartnern wichtig und Souveränität darüber, was Andere mit meinen Daten machen – die Wissenschaft betont freie Zugänglichkeit und Nachnutzbarkeit. FAIR Data Spaces verbinden beides auf Grundlage gemeinsamer Prinzipien.
Was muss getan werden, damit Datenaustausch nicht mehr bedeutet, E-Mail-Anhänge zu verschicken oder Geheimnisse zentralen Plattformen feindlicher Mächte anzuvertrauen? Wirtschaft, Wissenschaft und öffentliche Verwaltung suchen zunehmend nach Lösungen, um den Datenaustausch sicher und effizient zu gestalten und damit neues Innovationspotenzial zu heben. Was gibt es schon, was ist geplant, und wie können vorhandene Initiativen zusammenwachsen, um Daten über die Grenzen dieser Welten hinaus gemeinsam zu nutzen?
Initiativen der Wirtschaft wie Gaia-X und International Data Spaces priorisieren den Aufbau von Vertrauen unter Geschäftspartner:innen ohne Papier-Verträge sowie die Souveränität darüber, was Andere mit den eigenen wertvollen Daten machen. In der Wissenschaft, zum Beispiel bei der Nationalen Forschungsdateninfrastruktur NFDI, geht es um freie Zugänglichkeit und Nachnutzbarkeit im Einklang mit ethischen Prinzipien. Der öffentlichen Hand ist neben dem freien Zugang etwa zu Open-Data-Portalen die digitale Daseinsvorsorge wichtig. Große Herausforderungen unserer Zeit erfordern Datenaustausch nicht nur innerhalb dieser Welten, sondern über ihre Grenzen hinaus:
zum Beispiel zwischen Forschungsinstituten und kleinen Technologie-Unternehmen, die nicht alle Daten selbst sammeln können,
oder zwischen großen Unternehmen mit reichen Datenschätzen und wirtschaftlichen Interessen und einer Nutzung dieser Daten für das Gemeinwohl.
Das Projekt FAIR Data Spaces schafft Bausteine für übergreifende Datenräume als Keimzellen einer fairen Datenökonomie nach gemeinsamen Prinzipien. Wir möchten diskutieren, wie weit die aus dem Forschungsdatenmanagement stammenden FAIR-Data-Prinzipien tragen, wonach Daten findable (auffindbar), accessible (zugänglich), interoperabel und reusable (nachnutzbar) sein sollen. Das Projekt verfolgt den Plan, vorhandene Initiativen organisatorisch, rechtlich, technisch und praktisch zu einer gemeinsamen Community zusammenzuführen, und lebt dabei von einer breiten Mitwirkung. Werdet mit dem Fraunhofer IUK-Verbund Teil dieser Community und bleibt dabei innovativ und kritisch!
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...Christoph Lange
The Linked Data paradigm has emerged as a powerful enabler for data and knowledge interlinking and exchange using standardised Web technologies.
In this article, we discuss our vision how the Linked Data paradigm can be employed to evolve the intranets of large organisations -- be it enterprises, research organisations or governmental and public administrations -- into networks of internal data and knowledge.
In particular for large enterprises data integration is still a key challenge. The Linked Data paradigm seems a promising approach for integrating enterprise data. Like the Web of Data, which now complements the original document-centred Web, data intranets may help to enhance and flexibilise the intranets and service-oriented architectures that exist in large organisations. Furthermore, using Linked Data gives enterprises access to 50+ billion facts from the growing Linked Open Data (LOD) cloud. As a result, a data intranet can help to bridge the gap between structured data management (in ERP, CRM or SCM systems) and semi-structured or unstructured information in documents, wikis or web portals, and make all of these sources searchable in a coherent way.
Keynote at Baltic DB&IS 2014, 9 June 2014, Tallinn, Estonia
Linked Open (Geo)Data and the Distributed Ontology Language – a perfect matchChristoph Lange
The Distributed Ontology Language is a meta-language for integrating
ontologies written in different languages. Our notion of “distributed”
comprises logical heterogeneity within ontologies, modularity and reuse,
and links across ontologies in different places of the Web. Not only
can ontologies be distributed across the Web, but DOL's supply of
supported ontology languages can also be extended in a decentral way.
For this functionality, DOL builds on the Linked Open Data (LOD)
principles. But DOL also contributes to LOD use cases. Many current
LOD applications are limited by the weak expressivity of the RDF and
RDFS languages commonly used to express data and vocabularies.
Completely switching to a more expressive language would impair
scalability to big datasets. DOL addresses the scalability and
expressivity requirements by allowing to represent each aspect of a
dataset in the most suitable language and keeping these different
representations connected. This is particularly useful in geographic
information systems, where big datasets (e.g. Linked Geo Data, the LOD
version of OpenStreetMap) need to be integrated with formalisations of
complex spatial notions (e.g. in the first-order language Common Logic).
Linking Big Data to Rich Process DescriptionsChristoph Lange
Linked (Open) Data is one key to coping with Big Data: it enables decentralised, collaborative management of big datasets, low-overhead information retrieval, and scalable reasoning. Big Data are created or consumed by technical processes or business processes. Their formal description, e.g. for software verification or compliance checking, requires logics whose complexity far exceeds that of the data. Restricting LOD to the RDF logic does not allow for integrating rich process descriptions with the data that these processes create, and therefore does not enable knowledge management, information retrieval and reasoning to take full advantage of rich background knowledge. In this talk I demonstrate different frontiers at which I have worked towards achieving an integration of process descriptions and data.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
Annotating Rhetorical and Argumentative Structures in Mathematical Knowledge
1. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Annotating Rhetorical and Argumentative Structures
in Mathematical Knowledge
Summary of my work at DERI (Apr–Oct 2008)
EECS Seminar
Christoph Lange
Jacobs University, Bremen, Germany
KWARC – Knowledge Adaptation and Reasoning for Content
October 14, 2008
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 1
October Knowledge
2. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
My Home: Mathematical Knowledge Management
Ph. D. student with Prof. Michael Kohlhase
Our group does “Mathematical Knowledge Management”
dealing with mathematical knowledge
formality ranges from human-friendly to computer-verifiable
My Project
Collaboration on semiformal knowledge
Using semantic web technologies (a semantic wiki, in particular)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 2
October Knowledge
3. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
What I Wanted to Learn About the Semantic Web
engineering ontologies for scientific documents
user interfaces for annotating and browsing
relation of social interaction to knowledge
Where?
At DERI, they do this (and more)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 3
October Knowledge
4. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
DERI (Digital Enterprise Research Institute)
Largest semantic web research institute worldwide (130 members)
Applied Research
eLearning
semantic reality (sensor networks, ubiquitous computing)
web services
industrial applications
Semantic Information Systems and Language Engineering
Social Software
Foundational Research
data intensive infrastructures
information mining and retrieval
reasoning and querying
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 4
October Knowledge
5. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Before: SWiM, a Semantic Wiki for Mathematics
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 5
October Knowledge
6. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Ontologies for Mathematical Documents (1)
Previous State
notDef
I had a basic ontology that modelled structures of
renders-
mathematical knowledge; mainly statements (definition, Symbol
theorem, proof, examples) sym
used in SWiM for navigation, queries, internal uses- uses-
Symbol Symbol
bookkeeping
fmp ex
fmp ex
fmp ex
contains contains
symDef
symDef
symDef
contains
cd
cd
cd
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 6
October Knowledge
7. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Ontologies for Mathematical Documents (1)
Previous State
notDef
I had a basic ontology that modelled structures of
renders-
mathematical knowledge; mainly statements (definition, Symbol
theorem, proof, examples) sym
used in SWiM for navigation, queries, internal uses- uses-
Symbol Symbol
bookkeeping
fmp ex
fmp ex
fmp ex
Next Challenge
contains contains
Semi-formal knowledge often comes in documents that
also contain text symDef
symDef
symDef
There is a document structure (chapter, section, contains
cross-reference), and a rhetorical structure, both of
cd
cd
cd
which can be independent from the mathematical
structure.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 6
October Knowledge
8. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Ontologies for Mathematical Documents (2)
Getting the Model Right
rhetorical ont.
document ont. ↔ annotation ont. ↔
mathematical ont.
(following the SALT approach)
A
SALT (Semantically Annotated LTEX)
semantic authoring framework for creating scientific publications
Implementation
Expansion of the ontology
Rules for extracting these concepts from
OMDoc documents to RDF
Krextor XML→RDF extraction library
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 7
October Knowledge
9. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
User Interfaces for Annotating and Browsing
Improved Annotation Support
More and easier annotation support in the editor
toolbars for easy selection of types of mathematical knowledge
from phrase to theory level
deleting annotations
auto-completion of link targets (prepared)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 8
October Knowledge
10. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
User Interfaces for Annotating and Browsing
Improved Annotation Support
More and easier annotation support in the editor
toolbars for easy selection of types of mathematical knowledge
from phrase to theory level
deleting annotations
auto-completion of link targets (prepared)
Rhetorical Annotation and Visualisation
improved and extended syntax for annotating SALT-/RST-like
rhetorical structures in OMDoc
A
using the SALT ontology within the host language OMDoc, not LTEX
ideas for an editing interface
visualisation of rhetorical relations and blocks implemented
→ active documents
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 8
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11. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Annotation
Sections in the editor
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 9
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12. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Annotation
The toolbar
Sections in the editor
(Implementation by Gordan Ristovski)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 9
October Knowledge
13. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Visualisation of Rhetorical Structures
Rhetorical Blocks (SALT)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 10
October Knowledge
14. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Visualisation of Rhetorical Structures
Rhetorical Blocks (SALT)
Rhetorical Relations
(SALT, implementing RST)
(Implementation by Jana Giceva)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 10
October Knowledge
15. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Argumentation about Mathematical Knowledge
Idea
Need for structured wiki discussions, well-defined workflow for solving
problems with knowledge in a wiki
My Case
a wiki page is an item of mathematical knowledge, e. g. a theorem
issues discussed will be quite specific: e. g. “This theorem is hard to
understand” (or wrong, or inadequately presented, . . . )
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 11
October Knowledge
16. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Argumentation about Mathematical Knowledge
Idea
Need for structured wiki discussions, well-defined workflow for solving
problems with knowledge in a wiki
My Case
a wiki page is an item of mathematical knowledge, e. g. a theorem
issues discussed will be quite specific: e. g. “This theorem is hard to
understand” (or wrong, or inadequately presented, . . . )
Related Topic
There is also argumentation within artifacts of scientific knowledge, but so
far I focused more on argumentation about them.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 11
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17. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
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October Knowledge
18. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
October Knowledge
19. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
October Knowledge
20. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Idea Claire 2008–06–01 [Argument][Agree][Disagree][Decision]
So let’s make wiki discussions semantic!
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
October Knowledge
21. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Idea Claire 2008–06–01 [Argument][Agree][Disagree][Decision]
So let’s make wiki discussions semantic!
Argument Dave 2008–06–02 [Agree][Disagree]
We could take types from an argumentation ontology for the posts.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
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22. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Idea Claire 2008–06–01 [Argument][Agree][Disagree][Decision]
So let’s make wiki discussions semantic!
Argument Dave 2008–06–02 [Agree][Disagree]
We could take types from an argumentation ontology for the posts.
Argument Eric 2008–06–03 [Agree][Disagree]
And every discourse should be connected to resources corresponding to the wiki
page, and there should be domain-specific Idea and Issue subclasses.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
October Knowledge
23. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Idea Claire 2008–06–01 [Argument][Agree][Disagree][Decision]
So let’s make wiki discussions semantic!
Argument Dave 2008–06–02 [Agree][Disagree]
We could take types from an argumentation ontology for the posts.
Argument Eric 2008–06–03 [Agree][Disagree]
And every discourse should be connected to resources corresponding to the wiki
page, and there should be domain-specific Idea and Issue subclasses.
Agree Anonymous 2008–06–04
That’s great, then the wiki could assist with the realisation of an approved idea.
And old decisions would be documented.
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
October Knowledge
24. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Resource Edit Discussion History
Issue Alice 2008–05–30 [Idea][Argument][Agree][Disagree][Decision]
It’s hard to find out how to improve content (= resources) in wikis
Agree Bob 2008–05–31
Indeed, besides automated approaches it’s hard to get focused feedback from users.
Idea Claire 2008–06–01 [Argument][Agree][Disagree][Decision]
So let’s make wiki discussions semantic!
Argument Dave 2008–06–02 [Agree][Disagree]
We could take types from an argumentation ontology for the posts.
Argument Eric 2008–06–03 [Agree][Disagree]
And every discourse should be connected to resources corresponding to the wiki
page, and there should be domain-specific Idea and Issue subclasses.
Agree Anonymous 2008–06–04
That’s great, then the wiki could assist with the realisation of an approved idea.
And old decisions would be documented.
Decision Christoph 2008–06–05
So let’s do it! (Available in SWiM)
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 12
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25. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Domain-Specific Argumentation
Assumptions
Possible problems depend on the type of knowledge item
Possible solutions depend on the type of knowledge item and the type
of problem
Standard problems have standard solutions, with which software can
assist
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 13
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26. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Domain-Specific Argumentation
Assumptions
Possible problems depend on the type of knowledge item
Possible solutions depend on the type of knowledge item and the type
of problem
Standard problems have standard solutions, with which software can
assist
Survey (tinyurl.com/5qdetd)
Common issues: wrong, incomprehensible, uncommon style,
underspecified, redundant, truth uncertain
Common solutions: directly improve affected knowledge item, split it
When issues remain unresolved, it’s mostly due to insufficient
restructuring support
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 13
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27. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Domain-Specific Argumentation (Example)
User Interface
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 14
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28. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Domain-Specific Argumentation (Example)
hasDiscussion
forum1 theorem
(IkeWiki ontology)
has_container exemplifies
post1: Issue
(Incomprehensible) example
responseTo
has_reply resolvesInto
post2: Idea
(ProvideExample)
positionOn knowledge
post3: Agree items
(OMDoc ontology)
on wiki pages
post4: Disagree onIdea
post5: Agree onIssue
withPositions
post6: Decision
physical structure argumentative
(SIOC) discussion page structure
RDF Graph
User Interface
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 14
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29. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
General Argumentation on Social Media Sites
developing an argumentation module for SIOC
(ontology for Semantically Interlinking Online Communities)
joint work with Uldis Boj¯rs (SIOC) and Tudor Groza (SALT)
a
use cases, model, guidelines for usage
implementation and evaluation to be done
refers_to
supports/
Statement Argument
challenges
agrees_with/
subClassOf disagrees_with/ subClassOf
neutral_towards
arises_from
Issue Idea Elaboration Example Evaluation Justification
proposes_solution_for elaborates_on
decides Position
supported_by
Decision
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 15
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30. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
OpenMath Case Study
lightweight mathematical ontology engineering
(http://wiki.openmath.org)
no rhetorical structures, no documents
but still a lot of structures to annotate!
definitions, formal properties, examples, notations
local argumentation
small group of knowledge engineers (domain experts)
specialised editors: structured definitions, formulas, metadata
evaluation needed
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 16
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31. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Summary
What I hope(d) to learn – to use it for mathematical knowledge
management:
engineering ontologies for scientific documents !
user interfaces for annotating and browsing !
relation of social interaction to knowledge !
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 17
October Knowledge
32. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Summary
What I hope(d) to learn – to use it for mathematical knowledge
management:
engineering ontologies for scientific documents !
user interfaces for annotating and browsing !
relation of social interaction to knowledge !
What I hope to contribute to the semantic web:
mathematics as a complex use case pointing out limits of the
semantic web
an ontology for a complex domain, with document structure,
mathematical structure, and rhetorical structure
domain-specific argumentation
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 17
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33. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Further Work
Active Documents
Interactive editing and previewing of notations
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 18
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34. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Further Work
Active Documents
Interactive editing and previewing of notations
Argumentation
Study relationship between argumentation within and about documents
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 18
October Knowledge
35. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Further Work
Active Documents
Interactive editing and previewing of notations
Argumentation
Study relationship between argumentation within and about documents
Ontologies
1 Scalable metadata syntax and semantics for OMDoc
→ import metadata vocabularies as theories
2 Document these vocabularies in OMDoc
3 Model them in OMDoc
4 Export them back to the semantic web
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 18
October Knowledge
36. Introduction Ontologies/Annotation Argumentation Case Study Summary Outlook
Further Work
Active Documents
Interactive editing and previewing of notations
Argumentation
Study relationship between argumentation within and about documents
Ontologies
1 Scalable metadata syntax and semantics for OMDoc
→ import metadata vocabularies as theories
2 Document these vocabularies in OMDoc
3 Model them in OMDoc
4 Export them back to the semantic web
Semantic Web Empowering MKM
Lange (Jacobs University) Annotating Rhetorical and Argumentative Structures in Mathematical 14, 2008 18
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