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Survey

Resilience in Knowledge Graph Embeddings

Authors: Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo

Published in: TGDK, Volume 3, Issue 2 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 2

Abstract

In recent years, knowledge graphs have gained interest and witnessed widespread applications in various domains, such as information retrieval, question-answering, recommendation systems, amongst others. Large-scale knowledge graphs to this end have demonstrated their utility in effectively representing structured knowledge. To further facilitate the application of machine learning techniques, knowledge graph embedding models have been developed. Such models can transform entities and relationships within knowledge graphs into vectors. However, these embedding models often face challenges related to noise, missing information, distribution shift, adversarial attacks, etc. This can lead to sub-optimal embeddings and incorrect inferences, thereby negatively impacting downstream applications. While the existing literature has focused so far on adversarial attacks on KGE models, the challenges related to the other critical aspects remain unexplored. In this paper, we, first of all, give a unified definition of resilience, encompassing several factors such as generalisation, in-distribution generalization, distribution adaption, and robustness. After formalizing these concepts for machine learning in general, we define them in the context of knowledge graphs. To find the gap in the existing works on resilience in the context of knowledge graphs, we perform a systematic survey, taking into account all these aspects mentioned previously. Our survey results show that most of the existing works focus on a specific aspect of resilience, namely robustness. After categorizing such works based on their respective aspects of resilience, we discuss the challenges and future research directions.

Cite as

Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo. Resilience in Knowledge Graph Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 2, pp. 1:1-1:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{sharma_et_al:TGDK.3.2.1,
  author =	{Sharma, Arnab and Kouagou, N'Dah Jean and Ngomo, Axel-Cyrille Ngonga},
  title =	{{Resilience in Knowledge Graph Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:38},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.2.1},
  URN =		{urn:nbn:de:0030-drops-248117},
  doi =		{10.4230/TGDK.3.2.1},
  annote =	{Keywords: Knowledge graphs, Resilience, Robustness}
}

Document

Survey

DOI: 10.4230/TGDK.2.1.3

Semantic Web: Past, Present, and Future

Authors: Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract

Ever since the vision was formulated, the Semantic Web has inspired many generations of innovations. Semantic technologies have been used to share vast amounts of information on the Web, enhance them with semantics to give them meaning, and enable inference and reasoning on them. Throughout the years, semantic technologies, and in particular knowledge graphs, have been used in search engines, data integration, enterprise settings, and machine learning. In this paper, we recap the classical concepts and foundations of the Semantic Web as well as modern and recent concepts and applications, building upon these foundations. The classical topics we cover include knowledge representation, creating and validating knowledge on the Web, reasoning and linking, and distributed querying. We enhance this classical view of the so-called "Semantic Web Layer Cake" with an update of recent concepts that include provenance, security and trust, as well as a discussion of practical impacts from industry-led contributions. We conclude with an outlook on the future directions of the Semantic Web. This is a living document. If you like to contribute, please contact the first author and visit: https://github.com/ascherp/semantic-web-primer

Cite as

Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal. Semantic Web: Past, Present, and Future. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 3:1-3:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{scherp_et_al:TGDK.2.1.3,
  author =	{Scherp, Ansgar and Groener, Gerd and \v{S}koda, Petr and Hose, Katja and Vidal, Maria-Esther},
  title =	{{Semantic Web: Past, Present, and Future}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:37},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.3},
  URN =		{urn:nbn:de:0030-drops-198607},
  doi =		{10.4230/TGDK.2.1.3},
  annote =	{Keywords: Linked Open Data, Semantic Web Graphs, Knowledge Graphs}
}

Document

Survey

DOI: 10.4230/TGDK.1.1.11

How Does Knowledge Evolve in Open Knowledge Graphs?

Authors: Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract

Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.

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Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs. How Does Knowledge Evolve in Open Knowledge Graphs?. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 11:1-11:59, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{polleres_et_al:TGDK.1.1.11,
  author =	{Polleres, Axel and Pernisch, Romana and Bonifati, Angela and Dell'Aglio, Daniele and Dobriy, Daniil and Dumbrava, Stefania and Etcheverry, Lorena and Ferranti, Nicolas and Hose, Katja and Jim\'{e}nez-Ruiz, Ernesto and Lissandrini, Matteo and Scherp, Ansgar and Tommasini, Riccardo and Wachs, Johannes},
  title =	{{How Does Knowledge Evolve in Open Knowledge Graphs?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{11:1--11:59},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.11},
  URN =		{urn:nbn:de:0030-drops-194855},
  doi =		{10.4230/TGDK.1.1.11},
  annote =	{Keywords: KG evolution, temporal KG, versioned KG, dynamic KG}
}

Document

Vision

DOI: 10.4230/TGDK.1.1.9

Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination

Authors: Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract

Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning How the output of AI systems can be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives.

Cite as

Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal. Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 9:1-9:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{ibanez_et_al:TGDK.1.1.9,
  author =	{Ib\'{a}\~{n}ez, Luis-Daniel and Domingue, John and Kirrane, Sabrina and Seneviratne, Oshani and Third, Aisling and Vidal, Maria-Esther},
  title =	{{Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{9:1--9:32},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.9},
  URN =		{urn:nbn:de:0030-drops-194839},
  doi =		{10.4230/TGDK.1.1.9},
  annote =	{Keywords: Trust, Accountability, Autonomy, AI, Knowledge Graphs}
}

Document

Vision

DOI: 10.4230/TGDK.1.1.10

Multilingual Knowledge Graphs and Low-Resource Languages: A Review

Authors: Lucie-Aimée Kaffee, Russa Biswas, C. Maria Keet, Edlira Kalemi Vakaj, and Gerard de Melo

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract

There is a lack of multilingual data to support applications in a large number of languages, especially for low-resource languages. Knowledge graphs (KG) could contribute to closing the gap of language support by providing easily accessible, machine-readable, multilingual linked data, which can be reused across applications. In this paper, we provide an overview of work in the domain of multilingual KGs with a focus on low-resource languages. We review the current state of multilingual KGs along with the different aspects that are crucial for creating KGs with language coverage in mind. Special consideration is given to challenges particular to low-resource languages in KGs. We further provide an overview of applications that yield multilingual KG information as well as downstream applications reusing such multilingual data. Finally, we explore open problems regarding multilingual KGs with a focus on low-resource languages.

Cite as

Lucie-Aimée Kaffee, Russa Biswas, C. Maria Keet, Edlira Kalemi Vakaj, and Gerard de Melo. Multilingual Knowledge Graphs and Low-Resource Languages: A Review. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 10:1-10:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{kaffee_et_al:TGDK.1.1.10,
  author =	{Kaffee, Lucie-Aim\'{e}e and Biswas, Russa and Keet, C. Maria and Vakaj, Edlira Kalemi and de Melo, Gerard},
  title =	{{Multilingual Knowledge Graphs and Low-Resource Languages: A Review}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{10:1--10:19},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.10},
  URN =		{urn:nbn:de:0030-drops-194845},
  doi =		{10.4230/TGDK.1.1.10},
  annote =	{Keywords: knowledge graphs, multilingual, low-resource languages, review}
}

Document

DOI: 10.4230/DagSemProc.08391.1

08391 Abstracts Collection – Social Web Communities

Authors: Harith Alani, Steffen Staab, and Gerd Stumme

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

From September 21st to September 26th 2008, the Dagstuhl Seminar 08391 ``Social Web Communities'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

Cite as

Harith Alani, Steffen Staab, and Gerd Stumme. 08391 Abstracts Collection – Social Web Communities. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{alani_et_al:DagSemProc.08391.1,
  author =	{Alani, Harith and Staab, Steffen and Stumme, Gerd},
  title =	{{08391 Abstracts Collection – Social Web Communities}},
  booktitle =	{Social Web Communities},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.1},
  URN =		{urn:nbn:de:0030-drops-17928},
  doi =		{10.4230/DagSemProc.08391.1},
  annote =	{Keywords: Social Web Communities, Social Network Analysis, Collaborative Tagging}
}

Document

DOI: 10.4230/DagSemProc.08391.2

08391 Executive Summary – Social Web Communities

Authors: Harith Alani, Steffen Staab, and Gerd Stumme

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software.

Cite as

Harith Alani, Steffen Staab, and Gerd Stumme. 08391 Executive Summary – Social Web Communities. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{alani_et_al:DagSemProc.08391.2,
  author =	{Alani, Harith and Staab, Steffen and Stumme, Gerd},
  title =	{{08391 Executive Summary – Social Web Communities}},
  booktitle =	{Social Web Communities},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.2},
  URN =		{urn:nbn:de:0030-drops-17864},
  doi =		{10.4230/DagSemProc.08391.2},
  annote =	{Keywords: }
}

Document

DOI: 10.4230/DagSemProc.08391.3

08391 Group Summary – Mining for Social Serendipity

Authors: Alexandre Passant, Ian Mulvany, Peter Mika, Nicolas Maisonneuve, Alexander Löser, Ciro Cattuto, Christian Bizer, Christian Bauckhage, and Harith Alani

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

A common social problem at an event in which people do not personally know all of the other participants is the natural tendency for cliques to form and for discussions to mainly happen between people who already know each other. This limits the possibility for people to make interesting new acquaintances and acts as a retarding force in the creation of new links in the social web. Encouraging users to socialize with people they don't know by revealing to them hidden surprising links could help to improve the diversity of interactions at an event. The goal of this paper is to propose a method for detecting extit{"surprising"} relationships between people attending an event. By extit{"surprising"} relationship we mean those relationships that are not known a-priori, and that imply shared information not directly related with the local context of the event (location, interests, contacts) at which the meeting takes place. To demonstrate and test our concept we used the Flickr community. We focused on a community of users associated with a social event (a computer science conference) and represented in Flickr by means of a photo pool devoted to the event. We use Flickr metadata (tags) to mine for user similarity not related to the context of the event, as represented in the corresponding Flickr group. For example, we look for two group members who have been in the same highly specific place (identified by means of geo-tagged photos), but are not friends of each other and share no other common interests or, social neighborhood.

Cite as

Alexandre Passant, Ian Mulvany, Peter Mika, Nicolas Maisonneuve, Alexander Löser, Ciro Cattuto, Christian Bizer, Christian Bauckhage, and Harith Alani. 08391 Group Summary – Mining for Social Serendipity. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{passant_et_al:DagSemProc.08391.3,
  author =	{Passant, Alexandre and Mulvany, Ian and Mika, Peter and Maisonneuve, Nicolas and L\"{o}ser, Alexander and Cattuto, Ciro and Bizer, Christian and Bauckhage, Christian and Alani, Harith},
  title =	{{08391 Group Summary – Mining for Social Serendipity}},
  booktitle =	{Social Web Communities},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.3},
  URN =		{urn:nbn:de:0030-drops-17910},
  doi =		{10.4230/DagSemProc.08391.3},
  annote =	{Keywords: Serendipity, online activity, context, ubiquitous computing}
}

Document

DOI: 10.4230/DagSemProc.08391.4

08391 Group Summary – The Berners-Lee Hypothesis: Power laws and Group Structure in Flickr

Authors: Andrea Baldassarri, Alain Barrat, Andrea Capocci, Harry Halpin, Ulrike Lehner, Jose Ramasco, Valentin Robu, and Dario Taraborelli

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

An intriguing hypothesis, first suggested by Tim Berners-Lee, is that the structure of online groups should conform to a power law distribution. We relate this hypothesis to earlier work around the Dunbar Number, which is a supposed limit to the number of social contacts a user can have in a group. As preliminary results, we show that the number of contacts of a typical Flickr user, the number of groups a user belongs to, and the size of Flickr groups all follow power law distributions. Furthermore, we find some unexpected differences in the internal structure of public and private Flickr groups. For further research, we further operationalize the Berners-Lee hypothesis to suppose that users with a group membership distribution that follows a power law will produce more content for social Web systems.

Cite as

Andrea Baldassarri, Alain Barrat, Andrea Capocci, Harry Halpin, Ulrike Lehner, Jose Ramasco, Valentin Robu, and Dario Taraborelli. 08391 Group Summary – The Berners-Lee Hypothesis: Power laws and Group Structure in Flickr. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{baldassarri_et_al:DagSemProc.08391.4,
  author =	{Baldassarri, Andrea and Barrat, Alain and Capocci, Andrea and Halpin, Harry and Lehner, Ulrike and Ramasco, Jose and Robu, Valentin and Taraborelli, Dario},
  title =	{{08391 Group Summary – The Berners-Lee Hypothesis: Power laws and Group Structure in Flickr}},
  booktitle =	{Social Web Communities},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.4},
  URN =		{urn:nbn:de:0030-drops-17893},
  doi =		{10.4230/DagSemProc.08391.4},
  annote =	{Keywords: Social group flickr powerlaw}
}

Document

DOI: 10.4230/DagSemProc.08391.5

08391 Group Summary – The Evolution and Dynamics of Research Networks

Authors: Vladimir Batagelj, Bettina Hoser, Claudia Müller, Steffen Staab, and Gerd Stumme

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

Existing collaboration and innovation in scientific communities can be enhanced by understanding the underlying patterns und hidden relations. Social network analysis is an appropriate method to reveal such patterns. Nevertheless, research in this area is mainly focused on social networks. One promising approach is to use homophily networks as well. Furthermore, extending the static to a dynamic network model enables to understand existing interdependencies in these networks. A mathematical description of possible analyses is given. Finally, resulting research questions are illustrated and the necessity of an interdisciplinary research approach is pointed out.

Cite as

Vladimir Batagelj, Bettina Hoser, Claudia Müller, Steffen Staab, and Gerd Stumme. 08391 Group Summary – The Evolution and Dynamics of Research Networks. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{batagelj_et_al:DagSemProc.08391.5,
  author =	{Batagelj, Vladimir and Hoser, Bettina and M\"{u}ller, Claudia and Staab, Steffen and Stumme, Gerd},
  title =	{{08391 Group Summary – The Evolution and Dynamics of Research  Networks}},
  booktitle =	{Social Web Communities},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.5},
  URN =		{urn:nbn:de:0030-drops-17906},
  doi =		{10.4230/DagSemProc.08391.5},
  annote =	{Keywords: Homophily networks, social networks, evolution, scientific community}
}

Document

DOI: 10.4230/DagSemProc.08391.6

08391 Working Group Summary – Analyzing Tag Semantics Across Tagging Systems

Authors: Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov, and Martin Szomszor

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.

Cite as

Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov, and Martin Szomszor. 08391 Working Group Summary – Analyzing Tag Semantics Across Tagging Systems. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{benz_et_al:DagSemProc.08391.6,
  author =	{Benz, Dominik and Grobelnik, Marko and Hotho, Andreas and J\"{a}schke, Robert and Mladenic, Dunja and Servedio, Vito D. P. and Sizov, Sergej and Szomszor, Martin},
  title =	{{08391 Working Group Summary – Analyzing Tag Semantics Across Tagging Systems}},
  booktitle =	{Social Web Communities},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.6},
  URN =		{urn:nbn:de:0030-drops-17854},
  doi =		{10.4230/DagSemProc.08391.6},
  annote =	{Keywords: Social Web Communities, Folksonomy, Tag, Semantics}
}

Document

DOI: 10.4230/DagSemProc.08391.7

A Short Note on Social-Semiotic Networks from the Point of View of Quantitative Semantics

Authors: Alexander Mehler

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

In this extended abstract we discuss four related characteristics of semantic spaces as the standard model of meaning representation in quantitative semantics. We argue that these characteristics are challenged from the point of view of social web communities and the possibilities which they offer in terms of exploring semantic emph{and} pragmatic data. More specifically, we plead for a reconstruction of the weak contextual hypothesis in order to account for non-linguistic, pragmatic aspects of context. Finally, we mention two consequences of such a pragmatic turn, that is, in the area of named entity recognition and of language evolution.

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Alexander Mehler. A Short Note on Social-Semiotic Networks from the Point of View of Quantitative Semantics. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{mehler:DagSemProc.08391.7,
  author =	{Mehler, Alexander},
  title =	{{A Short Note on Social-Semiotic Networks from the Point of View of Quantitative Semantics}},
  booktitle =	{Social Web Communities},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.7},
  URN =		{urn:nbn:de:0030-drops-17884},
  doi =		{10.4230/DagSemProc.08391.7},
  annote =	{Keywords: Semantic space, social web community, quantitative semantic weak contextual hypothesis}
}

Document

DOI: 10.4230/DagSemProc.08391.8

Information-Theoretic Models of Tagging

Authors: Harry Halpin

Published in: Dagstuhl Seminar Proceedings, Volume 8391, Social Web Communities (2008)

Abstract

In earlier work, we showed using Kulback-Leibler (KL) divergence that tags form a power law distribution very quickly. Yet there is one major observed deviation from the ideal power law distribution for the top 25 tags, a large "bump" in increased frequency for the top 7-10 tags. We originally hypothesized that the "bump" in the data could be caused by a preferential attachment mechanism. However, an experiment that tested both feedback and no-feedback conditions over tagging (200+ subjects) shows that the power law distribution arises regardless of any feedback effect. We hypothesize that an information-theoretic analysis of tags lead to a power law without feedback.

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Harry Halpin. Information-Theoretic Models of Tagging. In Social Web Communities. Dagstuhl Seminar Proceedings, Volume 8391, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{halpin:DagSemProc.08391.8,
  author =	{Halpin, Harry},
  title =	{{Information-Theoretic Models of Tagging}},
  booktitle =	{Social Web Communities},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8391},
  editor =	{Harith Alani and Steffen Staab and Gerd Stumme},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08391.8},
  URN =		{urn:nbn:de:0030-drops-17876},
  doi =		{10.4230/DagSemProc.08391.8},
  annote =	{Keywords: Tagging information theory feedback}
}

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