High-level fusion based on conceptual graphs

Laudy, Claire; Ganascia, Jean-Gabriel; Sedogbo, C.

doi:10.1109/icif.2007.4408028

Cited by 13 publications

(9 citation statements)

References 8 publications

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“…The connectivity of the resulting CGs thus depends on the number of common nodes. There are other techniques available for graph fusion based on the join operator [13,6], but this simple fusion operator based on coreferent nodes merge operator is sufficient in this case.…”

Section: Proposed Algorithmmentioning

confidence: 99%

CG2A: Conceptual Graphs Generation Algorithm

Faci

Lesot

Laudy

2021

Atlantis Studies in Uncertainty Modelling

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Conceptual Graphs (CGs) are a formalism to represent knowledge. The production of CG benchmarks is currently a crucial need in the community to validate algorithms. This paper proposes CG2A, an algorithm to build synthetic CGs exploiting most of their expressivity. CG2A takes as input constraints that constitute ontological knowledge including a vocabulary and a set of CGs with some label variables, called γ-CGs, as components of the generated CGs. Extensions also enable the automatic generation of the set of γ-CGs and vocabulary to ease the database generation and increase variability.

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Section: Proposed Algorithmmentioning

confidence: 99%

CG2A: Conceptual Graphs Generation Algorithm

Faci

Lesot

Laudy

2021

Atlantis Studies in Uncertainty Modelling

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“…fusability according to a model A model of the sougth-after situation may be defined, as stated in [8] and [9]. Then, the fusability testing has to take into account this model, and the potential additional fusability constraints that result from it.…”

Section: Fusability According To Graph Similarity Onlymentioning

confidence: 99%

Introducing semantic knowledge in high-level fusion

Laudy¹,

Ganascia

2009

MILCOM 2009 - 2009 IEEE Military Communications Conference

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The necessity of taking into account high-level information has recently been reported by the information fusion community. We previously presented an approach for high-level symbolic fusion that relies on the use of the conceptual graphs model. Domain knowledge is a major point of the fusion process. The use of conceptual graphs for knowledge representation eases the process of expressing domain knowledge and fusion heuristics. We use conceptual graphs in order to model a situation of interest. Information items extracted from different sources are fused, using the model of situation in order to orient the fusion by delivering a context. This article details a step that was introduced prior to fusion, that aims at testing the compatibility of observations. It explains the way the domain knowledge is introduced inside the compatibility test, similarly as it was previously introduced in the fusion process. The proposed approach is illustrated within the context of a decision support system for geopolitical crisis management.

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“…Finally, the type of considered news content and the exact application that multimodal fusion techniques support may vary among the relevant literature approaches. In [21], a generic approach to fusion is also proposed based on the use of conceptual graphs; however, the focus is on fusing TV program metadata such as program title and date, rather than semantic information coming from the analysis of the audio, visual, and so forth modalities. As a consequence, the developed formulation cannot handle uncertain input, for example, the fuzzy degrees of content-concept association that individual modality analysis techniques such as visual classifiers typically produce.…”

Section: Related Workmentioning

confidence: 99%

A System for the Semantic Multimodal Analysis of News Audio-Visual Content

Mezaris

Gidaros

Kasper

et al. 2010

EURASIP J. Adv. Signal Process.

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News-related content is nowadays among the most popular types of content for users in everyday applications. Although the generation and distribution of news content has become commonplace, due to the availability of inexpensive media capturing devices and the development of media sharing services targeting both professional and user-generated news content, the automatic analysis and annotation that is required for supporting intelligent search and delivery of this content remains an open issue. In this paper, a complete architecture for knowledge-assisted multimodal analysis of news-related multimedia content is presented, along with its constituent components. The proposed analysis architecture employs state-of-the-art methods for the analysis of each individual modality (visual, audio, text) separately and proposes a novel fusion technique based on the particular characteristics of news-related content for the combination of the individual modality analysis results. Experimental results on news broadcast video illustrate the usefulness of the proposed techniques in the automatic generation of semantic annotations.

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High-level fusion based on conceptual graphs

Cited by 13 publications

References 8 publications

CG2A: Conceptual Graphs Generation Algorithm

CG2A: Conceptual Graphs Generation Algorithm

Introducing semantic knowledge in high-level fusion

A System for the Semantic Multimodal Analysis of News Audio-Visual Content

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