Emergent Semantics Systems

Aberer, Karl

doi:10.1007/978-3-540-30145-5_2

Cited by 29 publications

(26 citation statements)

References 76 publications

(60 reference statements)

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“…For instance, (50, 1,20) could describe what a MSc student should do in order to write the state-of-the-art of his MSc thesis. Of course, this scenario does not fall into trialogical learning, but is rather an instance of monological learning (acquisition metaphor).…”

Section: Collaborative Literature Review and Annotationmentioning

confidence: 99%

“…In this context, the individual interactions of group members would lead to global effects that could be observed as emerging knowledge artifacts (related somehow to emergent semantics [1]). Ontologies would thus become an emergent effect of open-ended interactions within or across groups of individuals as opposed to be a firm commitment of a small group of domain experts (for more see [26]).…”

Section: Kb = An Rdf-based Repositorymentioning

confidence: 99%

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Emergent Knowledge Artifacts for Supporting Trialogical E-Learning

Tzitzikas

Christophides

Flouris

et al. 2007

International Journal of Web-Based Learning and Teaching Technologies

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Abstract. This paper elaborates on scenarios for collaborative knowledge creation in the spirit of the trialogical learning paradigm. According to these scenarios the group knowledge base is formed by combining the knowledge bases of the participants according to various methods. The provision of flexible methods for defining various aspects of the group knowledge is expected to enhance synergy in the knowledge creation process and could lead to the development of tools that overcome the inelasticities of the current knowledge creation practices. Subsequently, these scenarios are projected to various knowledge representation frameworks and for each one of them the paper analyzes and discusses related techniques and identifies issues that are worth further research.

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Section: Collaborative Literature Review and Annotationmentioning

confidence: 99%

Section: Kb = An Rdf-based Repositorymentioning

confidence: 99%

Emergent Knowledge Artifacts for Supporting Trialogical E-Learning

Tzitzikas

Christophides

Flouris

et al. 2007

International Journal of Web-Based Learning and Teaching Technologies

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“…Within a cooking peer-to-peer network remote peers exchange recipes documented as Topic Maps 1 . To collect information, peers send Topics which represent the Subjects of interest to remote peers.…”

Section: The Challenge In An Examplementioning

confidence: 99%

“…Basically, the issues discussed in this paper are strong related to the idea of emergent semantics [1].…”

Section: Related Workmentioning

confidence: 99%

Topic Map Exchange in the Absence of Shared Vocabularies

Maicher

2006

Lecture Notes in Computer Science

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Topic Maps are the international industry standard for semantic information integration. Appropriate means for Topic Map exchange are crucial for its success as integration technology. Topic Map exchange bases on the governing Subject Equality decision approach, the decision whether two Subject Proxies indicate identical Subjects. This paper discusses the 'absence of shared vocabularies' in the context of these decisions. Thereby, a differentiation between Referential and Structuralist Subject Equality decision approaches is introduced. All existing approaches to Topic Map exchange base on the TMDM. This implies a Referential Subject Equality decision approach and bound to a concrete Subject Map Disclosure (SMD) ontology and Subject Map (SM) vocabulary. This paper introduces a Structuralist Subject Equality decision approach which is called SIM. It allows the exchange of Topic Maps in the absence of a shared SM ontology and SM vocabulary. The challenge in an exampleWithin a cooking peer-to-peer network remote peers exchange recipes documented as Topic Maps 1 . To collect information, peers send Topics which represent the Subjects of interest to remote peers. In the cooking network a Subject might be 'roasted lamb loin'. The remote peers check the availability of information about this Subject and respond with an according Topic Map Fragment. Afterwards, the requesting peer integrates all remote recipes about roasting lamb loins into its local recipe collection.This works fine if all peers made agreements about how to describe lamb cuts correctly. What happens if a remote peer uses the term lamb saddle instead? Or roasted lamb leg chops? The resulting meals are identical, but the requesting peers will never receive their recipes from distance. This shows that two critical points arise, if semantic agreements are not made by all peers logging into the network: How to request knowledge from remote peers if shared vocabularies are not available? How to integrate (merge) the received information into the local Topic Map?The solution proposed in this paper allows peers to interact in networks without having the overhead of centrally enforced vocabularies. Our solution detects 1 To avoid ambiguities all terminology concerning Topic Map Technologies is capitalised.

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“…However, they are usually quite expensive and inflexible because they are created using human judgment [18].…”

Section: Ontology and Domain Hierarchiesmentioning

confidence: 99%