Download PDF Knowledge-Driven Multimedia Information Extraction and Ontology Evolution : Bridging the Semantic Gap
Knowledge-Driven Multimedia Information Extraction and Ontology Evolution : Bridging the Semantic Gap Georgios Paliouras
Published Date: 01 Nov 2011
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Original Languages: English
Format: Paperback::245 pages
ISBN10: 3642207944
ISBN13: 9783642207945
Publication City/Country: Berlin, Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Filename: knowledge-driven-multimedia-information-extraction-and-ontology-evolution-bridging-the-semantic-gap.pdf
Dimension: 155x 235x 20.32mm::397g
The goal of the Semantic Web is to create a network of data and knowledge that for ontology matching and alignment, versioning, evolution and modularisation. Ontology/schema/vocabulary-based information retrieval; Semantic Web (e.g. Solutions for bridging the gap between Web of Data and the Web of Services the images. The phenomenon is referred to as the semantic gap in the literature. Several knowledge-based methods have evolved [15] to address this issue. In this paper, we have presented a semantic knowledge management system of musical information, called SEMU. We have proposed a SEMU ontology as the central semantic model of this system. This ontology has been used to capture the extracted information from audio files and crawled web pages which were retrieved applying various techniques from the digital humanities to graph-based approaches. Walter and Tobias the current relevance of information extraction and semantic enrichment in a multilingual model for language evolution and show that knowledge representation must the ontological description of a named entity has remained quite elusive. Knowledge-Driven Multimedia Information Extraction and Ontology Evolution: Bridging the Semantic Gap | Georgios Paliouras (auth.), Georgios Paliouras The contents stem largely from the research work conducted over a period of three years under the framework of the research project BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction). The book is designed to provide researchers, practitioners, and students with basic knowledge and skills presenting a sound Representing temporal knowledge in the semantic web: In Proc. Of Intl' Conf. On Knowledge-Based Intelligent Information Multimedia Information Extraction and Ontology Evolution - Bridging the Semantic Gap, volume traction and Ontology Evolution - Bridging the Semantic Gap, volume 6050 of Lecture Notes in Ar-. to the same element in a Semantic Web knowledge-base (or ontology), in some cases creating a new Ontology-Based Information Extraction was pub-. Knowledge-Driven Multimedia Information Extraction and Ontology Evolution: Bridging the Semantic Gap (Lecture Notes in Computer Science / Lecture Notes in Annotation This book presents the state of the art in the areas of ontology evolution and knowledge-driven multimedia information extraction, placing an emphasis on how the two can be combined to bridge the semantic gap. The different views taken the two main approaches towards semantic to multimedia content due to the multiplicity of information levels involved, have NLP Techniques for Term Extraction and Ontology Population. In P. Buitelaar and P. Cimiano, editors, Bridging the Gap between Text and Knowledge - Selected Contributions to Ontology Learning and Population from Text. IOS Press, 2008. [Maynard et al. 09] D. Maynard, A. Funk, and W. Peters. More recently, data-driven, bottom-up approaches have been proposed that offer a quantitative analysis of the evolution of a research domain. The former and also to derive key findings in relation to the strengths and weaknesses of extraction and discovery, latent semantics, knowledge acquisition, ontology learning, -. Integration of numeric and symbolic information for semantic image interpretation Article type: Research Article. Authors:Donadello The main challenge in SII is bridging the so called semantic gap,which is the complex correlation between low-level image features and high-level semantic concepts. In recent years, it became clear that ontological knowledge about image context and Download this most popular ebook and read the Knowledge Driven Multimedia Information. Extraction And Ontology Evolution: Bridging The Semantic Gap Thus, to reach semantic analysis and knowledge mining from multimedia content, novel techniques, such as ontology-based information retrieval, are required. In this paper, a novel Semantic Web-based annotation system is presented 2011, Knowledge-Driven Multimedia Information Extraction and Ontology Evolution - 2018, Bridging the Semantic Gap in Image and Video Analysis - Chapter. BOEMIE 2006 Workshop on Ontology Evolution and Multimedia Information Extraction approaches that combine multimedia extraction and ontology evolution in a bootstrapping Knowledge driven multimedia analysis; Multimedia ontologies; Multimedia Bridging the gap between multimedia features and semantics Knowledge-driven multimedia information extraction and ontology evolution: bridging the semantic gap G Paliouras, CD Spyropoulos, G Tsatsaronis Springer Science & Business Media,2011 Bridging the Gap between Text and Knowledge, P. Buitelaar and P. Learning non-taxonomical semantic relations from domain texts Ontology Population and Enrichment: State of the Art,in proceeding of Knowledge-driven Multimedia Information Extraction and ontology evolution, LNAI 6050, 2011, Paliouras, Georgios. Knowledge-Driven Multimedia Information Extraction and Ontology Evolution Bridging the Semantic Gap / [electronic resource]:edited Co-editor of Springer volume for Multimedia Information Extraction, IEEE Transactions on Knowledge and Data Engineering, - Editorial board Exploiting Ontology Based Search and EHR Interoperability to Facilitate Clinical Trial Design Extraction and Ontology Evolution - Bridging the Semantic Gap. Knowledge-driven multimedia information extraction and ontology evolution:bridging the semantic gap. [Geōrgios Paliuras; Constantine D Spyropoulos; George Tsatsaronis;] Home. WorldCat Home About WorldCat Help. Search. Search for Library Items Search for Lists Search for Contacts Search for a Library. Create lists, bibliographies and reviews: or Search WorldCat. Find items in libraries near you. Advanced This book presents the state of the art in the areas of ontology evolution and knowledge-driven multimedia information extraction, placing an emphasis on how the two can be combined to bridge the semantic gap. This was also the goal of the EC-sponsored BOEMIE (Bootstrapping Ontology Evolution with editors, Knowledge-Driven Multimedia Information Extraction and Ontology Evolution Bridging the Semantic Gap, volume 6050 of Lecture Notes in Computer The Paperback of the Knowledge-Driven Multimedia Information Extraction and Ontology Evolution: Bridging the Semantic Gap Georgios Paliouras at research since many years, the closing of the semantic gap being seen as key to Web media needs to be annotated using a media ontology which supports volume 6050 of Knowledge-Driven Multimedia Information Extraction and Ontol- ogy Evolution: Bridging the Semantic Gap, chapter 8, pages 196 239. Springer
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