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Journal articles on the topic 'Semantic multimedia representation'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Mylonas, Phivos, Thanos Athanasiadis, Manolis Wallace, Yannis Avrithis, and Stefanos Kollias. "Semantic representation of multimedia content: Knowledge representation and semantic indexing." Multimedia Tools and Applications 39, no. 3 (2007): 293–327. http://dx.doi.org/10.1007/s11042-007-0161-4.

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Zhang, Hong, Yu Huang, Xin Xu, Ziqi Zhu, and Chunhua Deng. "Latent semantic factorization for multimedia representation learning." Multimedia Tools and Applications 77, no. 3 (2017): 3353–68. http://dx.doi.org/10.1007/s11042-017-5135-6.

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Duan, Yiping, Qiyuan Du, Xin Fang, et al. "Multimedia Semantic Communications: Representation, Encoding and Transmission." IEEE Network 37, no. 1 (2023): 44–50. http://dx.doi.org/10.1109/mnet.001.2200468.

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Wagenpfeil, Stefan, Paul Mc Kevitt, and Matthias Hemmje. "Towards Automated Semantic Explainability of Multimedia Feature Graphs." Information 12, no. 12 (2021): 502. http://dx.doi.org/10.3390/info12120502.

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Multimedia feature graphs are employed to represent features of images, video, audio, or text. Various techniques exist to extract such features from multimedia objects. In this paper, we describe the extension of such a feature graph to represent the meaning of such multimedia features and introduce a formal context-free PS-grammar (Phrase Structure grammar) to automatically generate human-understandable natural language expressions based on such features. To achieve this, we define a semantic extension to syntactic multimedia feature graphs and introduce a set of production rules for phrases

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Al-Khatib, W., Y. F. Day, A. Ghafoor, and P. B. Berra. "Semantic modeling and knowledge representation in multimedia databases." IEEE Transactions on Knowledge and Data Engineering 11, no. 1 (1999): 64–80. http://dx.doi.org/10.1109/69.755616.

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Petridis, K., S. Bloehdorn, C. Saathoff, et al. "Knowledge representation and semantic annotation of multimedia content." IEE Proceedings - Vision, Image, and Signal Processing 153, no. 3 (2006): 255. http://dx.doi.org/10.1049/ip-vis:20050059.

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Smith, Roger W., Dorota Kieronska, and Svetha Venkatesh. "Conceptual Representation for Multimedia Information." International Journal of Pattern Recognition and Artificial Intelligence 11, no. 02 (1997): 303–27. http://dx.doi.org/10.1142/s0218001497000147.

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Multimedia information is now routinely available in the forms of text, pictures, animation and sound. Although text objects are relatively easy to deal with (in terms of information search and retrieval), other information bearing objects (such as sound, images, animation) are more difficult to index. Our research is aimed at developing better ways of representing multimedia objects by using a conceptual representation based on Schank's conceptual dependencies. Moreover, the representation allows for users' individual interpretations to be embedded in the system. This will alleviate the probl

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Yang, Bo, and Ali R. Hurson. "Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases." Mobile Information Systems 1, no. 4 (2005): 253–73. http://dx.doi.org/10.1155/2005/317136.

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Multimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity. To provide an efficient platform for multimedia retrieval, we propose to cluster ad hoc multimedia databases based on their semantic contents, and construct a virtual hierarchical indexing infrastructure overlaid on the mobile databases. This content-aware clustering scheme uses a semantic-aware fr

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Chang, Xiaojun, Zhigang Ma, Yi Yang, Zhiqiang Zeng, and Alexander G. Hauptmann. "Bi-Level Semantic Representation Analysis for Multimedia Event Detection." IEEE Transactions on Cybernetics 47, no. 5 (2017): 1180–97. http://dx.doi.org/10.1109/tcyb.2016.2539546.

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Jaitly, Shilpa, Vijay Laxmi, and Gagan Jindal. "Content-Based Image Retrieval and Feature Extraction: Analysing the Literature." International Journal for Research Publication and Seminar 15, no. 3 (2024): 357–73. http://dx.doi.org/10.36676/jrps.v15.i3.1520.

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A significant amount of multimedia data consists of digital images, and multimedia content analysis is used in many real-world computer vision applications. Multimedia information, especially photos, has become much more complicated in the last several years. Every day, millions of photos are posted to various websites, such as Instagram, Facebook, and Twitter. Finding a suitable image in an archive is a difficult research subject for the field of computer vision. Most search engines use standard text-based techniques that depend on metadata and captions in order to fetch photos. Over the past

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Luan, Xi Dao, Yu Xiang Xie, Yi Hong Tan, Sai Hu, Zhi Ping Chen, and Jing Wang. "Description Logic Based Objects and Space Relations Representation." Applied Mechanics and Materials 48-49 (February 2011): 366–72. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.366.

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This theme focuses on representing and reasoning high-level semantic based on concepts and their space relations. As to multimedia data, such as image and video, acquiring, representing and retrieving high-level semantic information has been a confused problem for a long time. Without the support of knowledge database, it is an impossible mission to carry out the simple synonymous retrieval, let alone retrieving the abstract semantic. This paper proposes some algorithms to translate restored concepts and their relations into a Concept Semantic Network, which is visualized by SVG finally. The p

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Yokota, Masao. "Aware Computing in Spatial Language Understanding Guided by Cognitively Inspired Knowledge Representation." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/184103.

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Mental image directed semantic theory (MIDST) has proposed an omnisensory mental image model and its description languageLmd. This language is designed to represent and compute human intuitive knowledge of space and can provide multimedia expressions with intermediate semantic descriptions in predicate logic. It is hypothesized that such knowledge and semantic descriptions are controlled by human attention toward the world and therefore subjective to each human individual. This paper describesLmdexpression of human subjective knowledge of space and its application to aware computing in cross-m

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Penta, Antonio. "A multimedia semantic framework for image understanding and retrieval." Encyclopedia with Semantic Computing and Robotic Intelligence 01, no. 01 (2017): 1650001. http://dx.doi.org/10.1142/s2425038416500012.

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On the grounds, ontologies have been shown to be a powerful resource for the interpretation and translation of the terminological and semantic relationships within domains of interest but it is still unclear how they can be applied in the context of multimedia data. In this paper, we describe a framework which can capture and manage semantic information related to the multimedia data by modeling in the ontology their features. In particular, the proposed ontology-based framework is organized in the following way: at the lower levels, spatial objects, colors, shapes are represented, and semanti

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Lemos, Daniela Lucas da Silva, and Renato Rocha Souza. "Ontologies for Semantic Annotation: Proposal for an Ontological Multimedia Reference Model." KNOWLEDGE ORGANIZATION 51, no. 8 (2024): 561–81. https://doi.org/10.5771/0943-7444-2024-8-561.

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Recent years have seen considerable growth of online multimedia databases, largely due to digitization processes in different sectors of society. Knowledge organization and representation strategies were used to qualify and enrich data and metadata from different types of documents and ensure persistent and interoperable online information structures. This study aimed to propose an ontological reference model to systematically organize metadata that describes multimedia documents based on different contexts and needs. The proposed model was based on the NeOn methodology and aimed to encompass

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Afef, Zwidi, Ameni Yengui, and Neji Mahmoud. "Research system of semantic information in medical videoconference based on conceptual graphs and domain ontologies." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 7, no. 2 (2013): 979–99. http://dx.doi.org/10.24297/ijmit.v7i2.703.

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The multiplication of the number of AudioVisual Documents (AVD) engendered a problem while searching for information within gigantic databases of which we are incapable to index their contents completely manually. Indeed, several complex difficulties are put by these documents because of the vertiginous increase of the quantity of the multimedia data to be treated and the specification met in the representation and the extraction of their contents in particular semantics of the fact that these documents contain three types of media (text, sound, image). AVDs can be classified in professional b

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Latif, Afshan, Aqsa Rasheed, Umer Sajid, et al. "Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review." Mathematical Problems in Engineering 2019 (August 26, 2019): 1–21. http://dx.doi.org/10.1155/2019/9658350.

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Multimedia content analysis is applied in different real-world computer vision applications, and digital images constitute a major part of multimedia data. In last few years, the complexity of multimedia contents, especially the images, has grown exponentially, and on daily basis, more than millions of images are uploaded at different archives such as Twitter, Facebook, and Instagram. To search for a relevant image from an archive is a challenging research problem for computer vision research community. Most of the search engines retrieve images on the basis of traditional text-based approache

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Lemos, Daniela Lucas da Silva, and Renato Rocha Souza. "Knowledge Organization Systems for the Representation of Multimedia Resources on the Web: A Comparative Analysis." KNOWLEDGE ORGANIZATION 47, no. 4 (2020): 300–319. http://dx.doi.org/10.5771/0943-7444-2020-4-300.

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The lack of standardization in the production, organization and dissemination of information in documentation centers and institutions alike, as a result from the digitization of collections and their availability on the internet has called for integration efforts. The sheer availability of multimedia content has fostered the development of many distinct and, most of the time, independent metadata standards for its description. This study aims at presenting and comparing the existing standards of metadata, vocabularies and ontologies for multimedia annotation and also tries to offer a syntheti

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Cai, Liewu, Lei Zhu, Hongyan Zhang, and Xinghui Zhu. "DA-GAN: Dual Attention Generative Adversarial Network for Cross-Modal Retrieval." Future Internet 14, no. 2 (2022): 43. http://dx.doi.org/10.3390/fi14020043.

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Cross-modal retrieval aims to search samples of one modality via queries of other modalities, which is a hot issue in the community of multimedia. However, two main challenges, i.e., heterogeneity gap and semantic interaction across different modalities, have not been solved efficaciously. Reducing the heterogeneous gap can improve the cross-modal similarity measurement. Meanwhile, modeling cross-modal semantic interaction can capture the semantic correlations more accurately. To this end, this paper presents a novel end-to-end framework, called Dual Attention Generative Adversarial Network (D

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Yuan, Xu, Hua Zhong, Zhikui Chen, Fangming Zhong, and Yueming Hu. "Multimedia Feature Mapping and Correlation Learning for Cross-Modal Retrieval." International Journal of Grid and High Performance Computing 10, no. 3 (2018): 29–45. http://dx.doi.org/10.4018/ijghpc.2018070103.

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This article describes how with the rapid increasing of multimedia content on the Internet, the need for effective cross-modal retrieval has attracted much attention recently. Many related works ignore the latent semantic correlations of modalities in the non-linear space and the extraction of high-level modality features, which only focuses on the semantic mapping of modalities in linear space and the use of low-level artificial features as modality feature representation. To solve these issues, the authors first utilizes convolutional neural networks and topic modal to obtain a high-level se

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Alti, Adel, Sébastian Laborie, and Philippe Roose. "A Community-Based Semantic Social Context-Aware Driven Adaptation for Multimedia Documents." International Journal of Virtual Communities and Social Networking 7, no. 2 (2015): 31–49. http://dx.doi.org/10.4018/ijvcsn.2015040102.

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This paper presents an approach to enhance users experience through the use of recommendations and social networks for on-the-fly (at runtime) adaptation of multimedia documents. This paper presents also CSSAP, a dynamic service selection and assembly tool based on new user profiles and community profiles defined as set of semantic metadata, which context, quality of service and quality of experience parameters. The tool is based on community-aware semantic services and offer architecture, with three layers (semantic query, community management and semantic services). The most innovative chara

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Kollia, Ilianna, Nikolaos Simou, Andreas Stafylopatis, and Stefanos Kollias. "SEMANTIC IMAGE ANALYSIS USING A SYMBOLIC NEURAL ARCHITECTURE." Image Analysis & Stereology 29, no. 3 (2010): 159. http://dx.doi.org/10.5566/ias.v29.p159-172.

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Image segmentation and classification are basic operations in image analysis and multimedia search which have gained great attention over the last few years due to the large increase of digital multimedia content. A recent trend in image analysis aims at incorporating symbolic knowledge representation systems and machine learning techniques. In this paper, we examine interweaving of neural network classifiers and fuzzy description logics for the adaptation of a knowledge base for semantic image analysis. The proposed approach includes a formal knowledge component, which, assisted by a reasonin

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ORIA, VINCENT, and M. TAMER ÖZSU. "VIEWS OR POINTS OF VIEW ON IMAGES." International Journal of Image and Graphics 03, no. 01 (2003): 55–79. http://dx.doi.org/10.1142/s0219467803000919.

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Images like other multimedia data need to be described as it is difficult to grasp their semantics from the raw data. With the emergence of standards like MPEG-7, multimedia data will be increasingly produced together with some semantic descriptors. But a description of a multimedia data is just an interpretation, a point of view on the data and different interpretations can exist for the same multimedia data. In this paper we explore the use of view techniques to define and manage different points of view on images. Views have been widely used in relational database management systems to exte

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Ha, Hsin-Yu, Fausto C. Fleites, and Shu-Ching Chen. "Content-Based Multimedia Retrieval Using Feature Correlation Clustering and Fusion." International Journal of Multimedia Data Engineering and Management 4, no. 2 (2013): 46–64. http://dx.doi.org/10.4018/jmdem.2013040103.

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Nowadays, only processing visual features is not enough for multimedia semantic retrieval due to the complexity of multimedia data, which usually involve a variety of modalities, e.g. graphics, text, speech, video, etc. It becomes crucial to fully utilize the correlation between each feature and the target concept, the feature correlation within modalities, and the feature correlation across modalities. In this paper, the authors propose a Feature Correlation Clustering-based Multi-Modality Fusion Framework (FCC-MMF) for multimedia semantic retrieval. Features from different modalities are com

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Wagenpfeil, Stefan. "Multimedia Graph Codes for Fast and Semantic Retrieval-Augmented Generation." Electronics 14, no. 12 (2025): 2472. https://doi.org/10.3390/electronics14122472.

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Retrieval-Augmented Generation (RAG) has become a central approach to enhance the factual consistency and domain specificity of large language models (LLMs) by incorporating external context at inference time. However, most existing RAG systems rely on dense vector-based similarity, which fails to capture complex semantic structures, relational dependencies, and multimodal content. In this paper, we introduce Graph Codes—a matrix-based encoding of Multimedia Feature Graphs—as an alternative retrieval paradigm. Graph Codes preserve semantic topology by explicitly encoding entities and their typ

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Jiao, Sai-Mei, Hai-feng Wang, Kun Zhang, and Ya-qi Hu. "Neural Linguistic Steganalysis via Multi-Head Self-Attention." Journal of Electrical and Computer Engineering 2021 (April 17, 2021): 1–5. http://dx.doi.org/10.1155/2021/6668369.

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Linguistic steganalysis can indicate the existence of steganographic content in suspicious text carriers. Precise linguistic steganalysis on suspicious carrier is critical for multimedia security. In this paper, we introduced a neural linguistic steganalysis approach based on multi-head self-attention. In the proposed steganalysis approach, words in text are firstly mapped into semantic space with a hidden representation for better modeling the semantic features. Then, we utilize multi-head self-attention to model the interactions between words in carrier. Finally, a softmax layer is utilized

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Gvishiani, N. B. "A MULTIMODAL ‘TEXT’: THE LINGUOPRAGMATIC PECULIARITIES OF VERBAL AND NON-VERBAL COMPONENTS INTERACTING IN DIFFERENT COMMUNICATIVE TYPES OF DISCOURSE." Voprosy Kognitivnoy Lingvistiki, no. 1 (2023): 15–17. http://dx.doi.org/10.20916/1812-3228-2022-15-17.

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The article dwells on the interaction of verbal and non-verbal components in different communicative media - painting, filmography, and art-reviews discourse. In modern art, we come across various ‘mixed media’ in creating visual or moving images, which may also include the verbal component. The power of linguistic discourse is then applied in the spheres where traditionally other modes were found to prevail. In conceptualism, the word becomes a means of reflection and in neo surrealism - it fills expressive narratives growing into illocutionary speech acts. In the article, text is considered

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De Masi, A. "DIGITAL DOCUMENTATION’S ONTOLOGY: CONTEMPORARY DIGITAL REPRESENTATIONS AS EXPRESS AND SHARED MODELS OF REGENERATION AND RESILIENCE IN THE PLATFORM BIM/CONTAMINATED HYBRID REPRESENTATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-M-1-2021 (August 28, 2021): 189–97. http://dx.doi.org/10.5194/isprs-archives-xlvi-m-1-2021-189-2021.

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Abstract. The study illustrates a university research project of “Digital Documentation’s Ontology”, to be activated with other universities, of an Platform (P) – Building Information Modeling (BIM) articulated on a Contaminated Hybrid Representation (diversification of graphic models); the latter, able to foresee categories of Multi-Representations that interact with each other for to favour several representations, adapted to a different information density in the digital multi-scale production, is intended as platform (grid of data and information at different scales, semantic structure fro

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Bogdanova, Galina, Todor Todorov, Nikolay Noev, and Stefka Kancheva. "Research on Linguistic Approaches, Used for Semantic Explanation of Bell’s Knowledge." Digital Presentation and Preservation of Cultural and Scientific Heritage 2 (September 30, 2012): 155–60. http://dx.doi.org/10.55630/dipp.2012.2.7.

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This paper presents a research of linguistic structure of Bulgarian bells knowledge. The idea of building semantic structure of Bulgarian bells appeared during the “Multimedia fund – BellKnow” project. In this project was collected a lots of data about bells, their structure, history, technical data, etc. This is the first attempt for computation linguistic explain of bell knowledge and deliver a semantic representation of that knowledge. Based on this research some linguistic components, aiming to realize different types of analysis of text objects are implemented in term dictionaries. Thus,

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Zhu, Xinghui, Liewu Cai, Zhuoyang Zou, and Lei Zhu. "Deep Multi-Semantic Fusion-Based Cross-Modal Hashing." Mathematics 10, no. 3 (2022): 430. http://dx.doi.org/10.3390/math10030430.

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Due to the low costs of its storage and search, the cross-modal retrieval hashing method has received much research interest in the big data era. Due to the application of deep learning, the cross-modal representation capabilities have risen markedly. However, the existing deep hashing methods cannot consider multi-label semantic learning and cross-modal similarity learning simultaneously. That means potential semantic correlations among multimedia data are not fully excavated from multi-category labels, which also affects the original similarity preserving of cross-modal hash codes. To this e

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Farhan, S., M. A. Fahiem, and H. Tauseef. "On the Design of a Content based Image Retrieval System." Nucleus 56, no. 1 (2019): 36–41. https://doi.org/10.71330/thenucleus.2019.354.

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With the abundance of multimedia content on the World Wide Web, research and learning of effectivefeature representation and similarity measures have become crucial. Image searching poses severalchallenges. Lately, many researchers have been exploring the field. Automatic annotation of imagesbased on digital content processing proves to be an encouraging direction in the field. Content basedimage retrieval system development is an emerging field. Accuracy of the results of semantic searchdepends on the understanding of searcherâ€™s purpose, the meaning of conditions imposed in the searchquery

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Zhang, Ruiping. "A Personalized Course Resource Recommendation Method Based on Deep Learning in an Online Multi-Modal Multimedia Education Cloud Platform." International Journal of Information Technologies and Systems Approach 16, no. 2 (2023): 1–14. http://dx.doi.org/10.4018/ijitsa.319344.

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Aiming at the problem that unstructured text in online multi-modal multimedia education is easy to cause error propagation, this paper proposes a personalized course resource recommendation method using deep learning in online multi-modal multimedia education cloud platform. First, the word vector of the text is obtained from the course data set by using the BERT pre-training model, and its semantic information in different contexts is analyzed. Then, the more complex representation of each word is extracted through the long short-term memory network (LSTM), in which the multi-head attention l

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Sancho, Pilar, Iván Martínez, and Baltasar Fernández-Manjón. "Semantic Web Technologies Applied to e-learning Personalization in ." JUCS - Journal of Universal Computer Science 11, no. (9) (2005): 1470–81. https://doi.org/10.3217/jucs-011-09-1470.

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Despite the increasing importance gained by e-learning standards in the past few years, and the unquestionable goals reached (mainly regarding interoperability among e-learning contents) current e-learning standards are yet not sufficiently aware of the context of the learner. This means that only a limited support for adaptation regarding individual characteristics is currently being provided. In this article, we propose the use of semantic metadata for Learning Object (LO) contextualization in order to adapt instruction to the learner's cognitive requirements in three different ways: backgro

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Wu, Xiao-Ming, Xin Luo, Yu-Wei Zhan, Chen-Lu Ding, Zhen-Duo Chen, and Xin-Shun Xu. "Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 4263–71. http://dx.doi.org/10.1609/aaai.v36i4.20346.

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With the vigorous development of multimedia equipments and applications, efficient retrieval of large-scale multi-modal data has become a trendy research topic. Thereinto, hashing has become a prevalent choice due to its retrieval efficiency and low storage cost. Although multi-modal hashing has drawn lots of attention in recent years, there still remain some problems. The first point is that existing methods are mainly designed in batch mode and not able to efficiently handle streaming multi-modal data. The second point is that all existing online multi-modal hashing methods fail to effective

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Sujatha, Dr K., Koulik Ghsoh, and Aneesh Anand. "Domain Adaptation and Semantic Drawing Driven Sketch-to-Photo Retrieval using Collaborative Generative Representation Learning." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 1473–80. http://dx.doi.org/10.22214/ijraset.2024.61734.

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Abstract: Sketch-based face recognition is an interesting task in vision and multimedia research yet it is quite challenging due to the great difference between face photos and sketches. In this paper we propose a novel approach for photo-sketch generation aiming to automatically transform face photos into detail-preserving personal sketches. Unlike the traditional models synthesizing sketches based on a dictionary of exemplars we develop a fully convolutional network to learn the end-to-end photosketch mapping. Our approach takes whole face photos as inputs and directly generates the correspo

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Stella, Massimo, Michael S. Vitevitch, and Federico Botta. "Cognitive Networks Extract Insights on COVID-19 Vaccines from English and Italian Popular Tweets: Anticipation, Logistics, Conspiracy and Loss of Trust." Big Data and Cognitive Computing 6, no. 2 (2022): 52. http://dx.doi.org/10.3390/bdcc6020052.

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Monitoring social discourse about COVID-19 vaccines is key to understanding how large populations perceive vaccination campaigns. This work reconstructs how popular and trending posts framed semantically and emotionally COVID-19 vaccines on Twitter. We achieve this by merging natural language processing, cognitive network science and AI-based image analysis. We focus on 4765 unique popular tweets in English or Italian about COVID-19 vaccines between December 2020 and March 2021. One popular English tweet contained in our data set was liked around 495,000 times, highlighting how popular tweets

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Zhai, Xiaohua, Yuxin Peng, and Jianguo Xiao. "Heterogeneous Metric Learning with Joint Graph Regularization for Cross-Media Retrieval." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (2013): 1198–204. http://dx.doi.org/10.1609/aaai.v27i1.8464.

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As the major component of big data, unstructured heterogeneous multimedia content such as text, image, audio, video and 3D increasing rapidly on the Internet. User demand a new type of cross-media retrieval where user can search results across various media by submitting query of any media. Since the query and the retrieved results can be of different media, how to learn a heterogeneous metric is the key challenge. Most existing metric learning algorithms only focus on a single media where all of the media objects share the same data representation. In this paper, we propose a joint graph regu

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Zabulis, Xenophon, Nikolaos Partarakis, Valentina Bartalesi, et al. "Multimodal Dictionaries for Traditional Craft Education." Multimodal Technologies and Interaction 8, no. 7 (2024): 63. http://dx.doi.org/10.3390/mti8070063.

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We address the problem of systematizing the authoring of digital dictionaries for craft education from ethnographic studies and recordings. First, we present guidelines for the collection of ethnographic data using digital audio and video and identify terms that are central in the description of crafting actions, products, tools, and materials. Second, we present a classification scheme for craft terms and a way to semantically annotate them, using a multilingual and hierarchical thesaurus, which provides term definitions and a semantic hierarchy of these terms. Third, we link ethnographic res

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WANG, ZHIYONG, ZHERU CHI, DAGAN FENG, and AH CHUNG TSOI. "CONTENT-BASED IMAGE RETRIEVAL WITH RELEVANCE FEEDBACK USING ADAPTIVE PROCESSING OF TREE-STRUCTURE IMAGE REPRESENTATION." International Journal of Image and Graphics 03, no. 01 (2003): 119–43. http://dx.doi.org/10.1142/s0219467803000944.

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Content-based image retrieval has become an essential technique in multimedia data management. However, due to the difficulties and complications involved in the various image processing tasks, a robust semantic representation of image content is still very difficult (if not impossible) to achieve. In this paper, we propose a novel content-based image retrieval approach with relevance feedback using adaptive processing of tree-structure image representation. In our approach, each image is first represented with a quad-tree, which is segmentation free. Then a neural network model with the Back-

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Yu, Jing, Zhao Lu, Shoulin Yin, and Mirjana Ivanovic. "News recommendation model based on encoder graph neural network and bat optimization in online social multimedia art education." Computer Science and Information Systems, no. 00 (2024): 25. http://dx.doi.org/10.2298/csis231225025y.

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At present, the existing news recommendation system fails to fully consider the semantic information of news, meanwhile, the uneven popularity of news will also cause the phenomenon of long tail. Therefore, we propose a novel news recommendation model based on encoder graph neural network and Bat optimization in online social networks. Firstly, Bat optimization algorithm is used to improve the effect of news clustering. Secondly, the concept of metadata is introduced into the graph neural network, and the ontology of learning resources based on knowledge points is established to realize the co

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MIRENKOV, NIKOLAY, ALEXANDER VAZHENIN, RENTARO YOSHIOKA, TSUKASA EBIHARA, TETSUYA HIROTOMI, and TATIANA MIRENKOVA. "SELF-EXPLANATORY COMPONENTS: A NEW PROGRAMMING PARADIGM." International Journal of Software Engineering and Knowledge Engineering 11, no. 01 (2001): 5–36. http://dx.doi.org/10.1142/s0218194001000414.

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A new multimedia programming paradigm is presented. It is based on a system of micro- and macro-icons (composite pictures) representing self-explanatory software components in a "film" format. A film is a series of color stills supported, if necessary, by text and sound. Each still is to represent a view of objects or processes. Each film is to represent a multiple view (an extended set of dynamic and/or static features) of objects or processes. A self-explanatory film means that the associated stills are organized and presented in such a way that the semantic richness of a computational schem

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Lai, Jingjuan, Hanxiong Chen, and Yuzuru Fujiwara. "An information-base system based on the self-organization of concepts represented by terms." Terminology 3, no. 2 (1996): 313–34. http://dx.doi.org/10.1075/term.3.2.05lai.

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Since multimedia information is complicated inform and vast in amount, conventional database-management systems or knowledge-base-management systems are hardly appropriate to store, manage, and utilize expertise effectively. A new type of information model is developed according to an analysis of the information used by specialists for research and development, and a prototype information-management system is implemented. The system consists of three parts: (1) flexible storage without special constraints on format and representation; (2) self-organization of terms by extracting semantic relat

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Rogushina, J. V. "Use of Ontology-based knowledge Organization Sysytems for WIKI Resources." PROBLEMS IN PROGRAMMING, no. 1 (March 2022): 023–33. http://dx.doi.org/10.15407/pp2022.01.023.

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The paper considers the theoretical foundations of knowledge organization systems (KOSs) in intelligent ontology-based applications. The aim of this study is to analyze the use of different types of KOSs to organize and improve the knowledge base of semantic Wiki resources that contain heterogeneous multimedia content of large volume and have a complex structure integrated knowledge from different domains. The dialects of the OWL ontology representation language and their expressiveness for representing special cases of ontologies used in KOSs are considered. The criteria for the classificatio

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Buchmann, Oliver, Maik Siegmund, Robert Kaden, and Frank Iden. "CITYTWIN – AI-based Decision Support System for Semantic Search and Analysis of Location-based Information for Urban and Site Planning." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W5-2024 (June 27, 2024): 63–69. http://dx.doi.org/10.5194/isprs-annals-x-4-w5-2024-63-2024.

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Abstract. The development of a knowledge-based decision support system for the evaluation and planning of location and urban development concepts was implemented. In order to achieve this goal, cross-domain ontologies were developed for interdisciplinary databases, which are then mapped in semantic networks. The exponential growth in computing power in the hardware sector alone can no longer solve this problem, but at the same time enables the application of new methods for storing and evaluating data. Essentially, it is no longer just about the digital recording of object properties in conven

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Zhao, Yanhaotian. "State of the Art in the Application of Multimodal Affective Methods for Comparative Analysis of Modal Deficits." Applied and Computational Engineering 174, no. 1 (2025): 1–9. https://doi.org/10.54254/2755-2721/2025.po24716.

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The advent of multimedia technology has precipitated a paradigm shift in the realm of human-computer interaction and affective computing, thus rendering multimodal emotion recognition a pivotal domain. However, the issue of modal absence, resulting from equipment failure or environmental interference in practical applications, significantly impacts the accuracy of emotion recognition. The objective of this paper is to analyse multimodal emotion recognition methods oriented to modal absence. The focus is on comparing and analysing the advantages and disadvantages of techniques such as generativ

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Rogushina, J. V., and I. J. Grishanova. "Ontological methods and tools for semantic extension of the media WIKI technology." PROBLEMS IN PROGRAMMING, no. 2-3 (September 2020): 061–73. http://dx.doi.org/10.15407/pp2020.02-03.061.

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Practical aspects of ontological approach to organization of intelligent Wiki-based information resources (IR) are considered. We analyze the main features, capabilities and limitations of MediaWiki as a technological platform for development of the Web-based information resource and suggest main directions of its refinement. We propose an abstract model of MediaWiki architecture that formalizes relations between the main components of this software environment and analyze the ways of its semantic extensions based on ontological representation of domain knowledge. An original algorithm of sema

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Ehab, Engy, Nahla Belal, and Yasser Omar. "Tri-FND: Multimodal Fake News Detection Using Triplet Transformer Models." Journal of Advanced Research in Applied Sciences and Engineering Technology 63, no. 1 (2025): 255–70. https://doi.org/10.37934/araset.63.1.255270.

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The prevalence of fake news accompanied by multimedia content on the internet presents a significant challenge for users attempting to discern its authenticity. Automatically identifying and classifying fake news is a crucial way for combating misinformation and maintain the integrity of information dissemination. This paper proposes a fake news detection approach that exploits multimodality's potential and integrates textual and visual data to improve the fake news classification system. The novel multimodal learning approach to fake news detection, which has been termed Tri-FND, uses triplet

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Strashko, Iryna V. "PHONETIC, LEXICAL, GRAMMATICAL, COGNITIVE, AND PRAGMATIC LEVELS OF THE LINGUISTIC PERSONALITY (BASED ON THE INTERVIEW FROM THE AUTHOR’S MULTIMEDIA CORPUS)." Scientific Journal of National Pedagogical Dragomanov University. Series 9. Current Trends in Language Development, no. 25 (June 30, 2023): 79–89. http://dx.doi.org/10.31392/npu-nc.series9.2023.25.06.

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The paper focuses on the analysis of the means of representation of the informant’s linguistic personality at phonetic, lexical, grammatical, cognitive, and pragmatic levels in the oral discourse. The material of the study is a transcript of an audio recording of one interview from the author’s multimedia corpus “Everyone has their own war”. The interview was recorded in the Ukrainian language in one of the most emotionally, psychologically, and physically difficult moments of the informant’s life. Despite a certain limitation of language material, the peculiarities of the speech manifestation

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Vishniakou, U. A., and A. P. Kovalev. "ONLINE-SERVICES AND INFORMATION TECHNOLOGIES IN DISTANCE LEARNING." «System analysis and applied information science», no. 4 (February 8, 2018): 66–71. http://dx.doi.org/10.21122/2309-4923-2017-4-66-71.

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The article deals with the analysis of distance learning (DL) methods, approaches, technologies, tools, the use as known online services so and developing the new ones. The terminology in area of DL is discussed and differences between correspondence course and DL are done. The development tendencies of distance learning are analyzed. Their technical and organization components are done. The course programs for DL are realizing by software which functions are shown. The typical lines of DL, their advances and lacks are conceded. As DL advances are self activity, individuality, independence and

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Scianna, A., and M. La Guardia. "GLOBE BASED 3D GIS SOLUTIONS FOR VIRTUAL HERITAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W10 (September 12, 2018): 171–77. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w10-171-2018.

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<p><strong>Abstract.</strong> During the last years, many solutions have been proposed for 3D Virtual Heritage representations. Recently, also new technologies for online gaming evolved, based on javascript libraries (WebGL), used to create and publish virtual interactive environments. They are based on recent Web browser’s functionalities, surpassing some limitations of VRML technologies. On the side of geospatial information, technology has evolved from desktop GIS to 2D WebGIS and globe applications. The use of globe applications is, today, very diffused due to its immedia

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Petrenko, M. G., O. V. Palagin, M. O. Boyko, and S. M. Matveyshyn. "Knowledge-Oriented Tool Complex for Developing Databases of Scientific Publications and Taking into account Semantic Web Technology." Control Systems and Computers, no. 3 (299) (2022): 11–28. http://dx.doi.org/10.15407/csc.2022.03.011.

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Introduction. The development of theories, methods, and algorithms for the discovery and formation of new knowledge has always occupied one of the central places for any researcher, especially if he is actively working on the creation of new scientific publications. It is known that there is no universal language for the formal description of concepts (knowledge) and systemology of transdisciplinary scientific research. And therefore, scientists face a number of priority problems, including the problem of significantly accelerating the receipt by a researcher of the cognitively structured info

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