Deliverable 4.5: Context-aware Content Interpretation
| Autor: | Kontopoulos, E., Darányi, Sándor, Wittek, Peter, Konstantinidis, K., Riga, M., Mitzias, P., Stavropoulos, T., Andreadis, S., Maronidis, A., Karakostas, A., Tachos, S., Kaltsa, V., Tsagiopoulu, M., Avgerinakis, K. |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Systemvetenskap
informationssystem och informatik med samhällsvetenskaplig inriktning Medievetenskap contextualisation Interaction Technologies Other Engineering and Technologies not elsewhere specified Communication Systems Information Systems Social aspects Interaktionsteknik concept drift semantic drift Datorsystem Computer Systems quantum-like systems ontologies Övrig annan teknik Kommunikationssystem Media Studies |
| Popis: | The current deliverable summarises the work conducted within task T4.5 of WP4, presenting our proposed approaches for contextualised content interpretation, aimed at gaining insightful contextualised views on content semantics. This is achieved through the adoption of appropriate context-aware semantic models developed within the project, and via enriching the semantic descriptions with background knowledge, deriving thus higher level contextualised content interpretations that are closer to human perception and appraisal needs. More specifically, the main contributions of the deliverable are the following: A theoretical framework using physics as a metaphor to develop different models of evolving semantic content. A set of proof-of-concept models for semantic drifts due to field dynamics, introducing two methods to identify quantum-like (QL) patterns in evolving information searching behaviour, and a QL model akin to particle-wave duality for semantic content classification. Integration of two specific tools, Somoclu for drift detection and Ncpol2spda for entanglement detection. An “energetic” hypothesis accounting for contextualized evolving semantic structures over time. A proposed semantic interpretation framework, integrating (a) an ontological inference scheme based on Description Logics (DL), (b) a rule-based reasoning layer built on SPARQL Inference Notation (SPIN), (c) an uncertainty management framework based on non-monotonic logics. A novel scheme for contextualized reasoning on semantic drift, based on LRM dependencies and OWL’s punning mechanism. An implementation of SPIN rules for policy and ecosystem change management, with the adoption of LRM preconditions and impacts. Specific use case scenarios demonstrate the context under development and the efficiency of the approach. Respective open-source implementations and experimental results that validate all the above.All these contributions are tightly interlinked with the other PERICLES work packages: WP2 supplies the use cases and sample datasets for validating our proposed approaches, WP3 provides the models (LRM and Digital Ecosystem models) that form the basis for our semantic representations of content and context, WP5 provides the practical application of the technologies developed to preservation processes, while the tools and algorithms presented in this deliverable can be deployed in combination with test scenarios, which will be part of the WP6 test beds. PERICLES |
| Databáze: | OpenAIRE |
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