1,591 research outputs found
Semantic levels of domain-independent commonsense knowledgebase for visual indexing and retrieval applications
Building intelligent tools for searching, indexing and retrieval applications is needed to congregate the rapidly increasing amount of visual data. This raised the need for building and maintaining ontologies and knowledgebases to support textual semantic representation of visual contents, which is an important block in these applications. This paper proposes a commonsense knowledgebase that forms the link between the visual world and its semantic textual representation. This domain-independent knowledge is provided at different levels of semantics by a fully automated engine that analyses, fuses and integrates previous commonsense knowledgebases. This knowledgebase satisfies the levels of semantic by adding two new levels: temporal event scenarios and psycholinguistic understanding. Statistical properties and an experiment evaluation, show coherency and effectiveness of the proposed knowledgebase in providing the knowledge needed for wide-domain visual applications
Ontologies on the semantic web
As an informational technology, the World Wide Web has enjoyed spectacular success. In just ten years it has transformed the way information is produced, stored, and shared in arenas as diverse as shopping, family photo albums, and high-level academic research. The “Semantic Web” was touted by its developers as equally revolutionary but has not yet achieved anything like the Web’s exponential uptake. This 17 000 word survey article explores why this might be so, from a perspective that bridges both philosophy and IT
Automatic semantic video annotation in wide domain videos based on similarity and commonsense knowledgebases
In this paper, we introduce a novel framework for automatic Semantic Video Annotation. As this framework detects possible events occurring in video clips, it forms the annotating base of video search engine. To achieve this purpose, the system has to able to operate on uncontrolled wide-domain videos. Thus, all layers have to be based on generic features.
This framework aims to bridge the "semantic gap", which is the difference between the low-level visual features and the human's perception, by finding videos with similar visual events, then analyzing their free text annotation to find a common area then to decide the best description for this new video using commonsense knowledgebases.
Experiments were performed on wide-domain video clips from the TRECVID 2005 BBC rush standard database. Results from these experiments show promising integrity between those two layers in order to find expressing annotations for the input video. These results were evaluated based on retrieval performance
Automatic annotation of bioinformatics workflows with biomedical ontologies
Legacy scientific workflows, and the services within them, often present
scarce and unstructured (i.e. textual) descriptions. This makes it difficult to
find, share and reuse them, thus dramatically reducing their value to the
community. This paper presents an approach to annotating workflows and their
subcomponents with ontology terms, in an attempt to describe these artifacts in
a structured way. Despite a dearth of even textual descriptions, we
automatically annotated 530 myExperiment bioinformatics-related workflows,
including more than 2600 workflow-associated services, with relevant
ontological terms. Quantitative evaluation of the Information Content of these
terms suggests that, in cases where annotation was possible at all, the
annotation quality was comparable to manually curated bioinformatics resources.Comment: 6th International Symposium on Leveraging Applications (ISoLA 2014
conference), 15 pages, 4 figure
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