Relevant bibliographies by topics / Social and multimedia data

Academic literature on the topic 'Social and multimedia data'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Social and multimedia data"

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Yu, Chen, Yiwen Zhong, Thomas Smith, Ikhyun Park, and Weixia Huang. "Visual Data Mining of Multimedia Data for Social and Behavioral Studies." Information Visualization 8, no. 1 (January 2009): 56–70. http://dx.doi.org/10.1057/ivs.2008.32.

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With advances in computing techniques, a large amount of high-resolution high-quality multimedia data (video and audio, and so on) has been collected in research laboratories in various scientific disciplines, particularly in cognitive and behavioral studies. How to automatically and effectively discover new knowledge from rich multimedia data poses a compelling challenge because most state-of-the-art data mining techniques can only search and extract pre-defined patterns or knowledge from complex heterogeneous data. In light of this challenge, we propose a hybrid approach that allows scientists to use data mining as a first pass, and then forms a closed loop of visual analysis of current results followed by more data mining work inspired by visualization, the results of which can be in turn visualized and lead to the next round of visual exploration and analysis. In this way, new insights and hypotheses gleaned from the raw data and the current level of analysis can contribute to further analysis. As a first step toward this goal, we implement a visualization system with three critical components: (1) a smooth interface between visualization and data mining; (2) a flexible tool to explore and query temporal data derived from raw multimedia data; and (3) a seamless interface between raw multimedia data and derived data. We have developed various ways to visualize both temporal correlations and statistics of multiple derived variables as well as conditional and high-order statistics. Our visualization tool allows users to explore, compare and analyze multi-stream derived variables and simultaneously switch to access raw multimedia data.
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Naaman, Mor. "Social multimedia: highlighting opportunities for search and mining of multimedia data in social media applications." Multimedia Tools and Applications 56, no. 1 (May 21, 2010): 9–34. http://dx.doi.org/10.1007/s11042-010-0538-7.

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Sperlì, Giancarlo, Flora Amato, Vincenzo Moscato, and Antonio Picariello. "Multimedia Social Network Modeling using Hypergraphs." International Journal of Multimedia Data Engineering and Management 7, no. 3 (July 2016): 53–77. http://dx.doi.org/10.4018/ijmdem.2016070104.

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In this paper the authors define a novel data model for Multimedia Social Networks (MSNs), i.e. networks that combine information on users belonging to one or more social communities together with the multimedia content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and to represent in a simple way all the different kinds of relationships that are typical of social networks and multimedia sharing systems, and in particular between multimedia contents, among users and multimedia content and among users themselves. Different applications (e.g. influence analysis, multimedia recommendation) can be then built on the top of the introduce data model thanks to the introduction of proper user and multimedia ranking functions. In addition, the authors provide a strategy for hypergraph learning from social data. Some preliminary experiments concerning efficiency and effectiveness of the proposed approach for analysis of Last.fm network are reported and discussed.
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Yang, Qing, Tigang Jiang, Wenjia Li, Guangchi Liu, Danda B. Rawat, and Jun Wu. "Editorial: Multimedia and Social Data Processing in Vehicular Networks." Mobile Networks and Applications 25, no. 2 (December 14, 2019): 620–22. http://dx.doi.org/10.1007/s11036-019-01432-2.

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Sang, Jitao, Yue Gao, Bing-kun Bao, Cees Snoek, and Qionghai Dai. "Recent advances in social multimedia big data mining and applications." Multimedia Systems 22, no. 1 (September 28, 2015): 1–3. http://dx.doi.org/10.1007/s00530-015-0482-5.

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Kim, Sul-Ho, Kwon-Jae An, Seok-Woo Jang, and Gye-Young Kim. "Texture feature-based text region segmentation in social multimedia data." Multimedia Tools and Applications 75, no. 20 (January 27, 2016): 12815–29. http://dx.doi.org/10.1007/s11042-015-3237-6.

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Yadav, Snehlata, and Namita Tiwari. "Privacy preserving data sharing method for social media platforms." PLOS ONE 18, no. 1 (January 20, 2023): e0280182. http://dx.doi.org/10.1371/journal.pone.0280182.

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Digital security as a service is a crucial aspect as it deals with user privacy provision and secure content delivery to legitimate users. Most social media platforms utilize end-to-end encryption as a significant security feature. However, multimedia data transmission in group communication is not encrypted. One of the most important objectives for a service provider is to send the desired multimedia data/service to only legitimate subscriber. Broadcast encryption is the most appropriate cryptographic primitive solution for this problem. Therefore, this study devised a construction called anonymous revocable identity-based broadcast encryption that preserves the privacy of messages broadcasted and the identity of legitimate users, where even revoked users cannot extract information about the user’s identity and sent data. The update key is broadcast periodically to non-revoked users, who can obtain the message using the update and decryption keys. A third-party can also revoke the users. It is proven that the proposed construction is semantically secure against IND-ID-CPA attacks and efficient in terms of computational cost and communication bandwidth.
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Garg, Muskan, and Mukesh Kumar. "Review on event detection techniques in social multimedia." Online Information Review 40, no. 3 (June 13, 2016): 347–61. http://dx.doi.org/10.1108/oir-08-2015-0281.

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Purpose – Social Media is one of the largest platforms to voluntarily communicate thoughts. With increase in multimedia data on social networking websites, information about human behaviour is increasing. This user-generated data are present on the internet in different modalities including text, images, audio, video, gesture, etc. The purpose of this paper is to consider multiple variables for event detection and analysis including weather data, temporal data, geo-location data, traffic data, weekday’s data, etc. Design/methodology/approach – In this paper, evolution of different approaches have been studied and explored for multivariate event analysis of uncertain social media data. Findings – Based on burst of outbreak information from social media including natural disasters, contagious disease spread, etc. can be controlled. This can be path breaking input for instant emergency management resources. This has received much attention from academic researchers and practitioners to study the latent patterns for event detection from social media signals. Originality/value – This paper provides useful insights into existing methodologies and recommendations for future attempts in this area of research. An overview of architecture of event analysis and statistical approaches are used to determine the events in social media which need attention.
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Amato, Flora, Giovanni Cozzolino, and Giancarlo Sperlì. "A Hypergraph Data Model for Expert-Finding in Multimedia Social Networks." Information 10, no. 6 (May 28, 2019): 183. http://dx.doi.org/10.3390/info10060183.

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Online Social Networks (OSNs) have found widespread applications in every area of our life. A large number of people have signed up to OSN for different purposes, including to meet old friends, to choose a given company, to identify expert users about a given topic, producing a large number of social connections. These aspects have led to the birth of a new generation of OSNs, called Multimedia Social Networks (MSNs), in which user-generated content plays a key role to enable interactions among users. In this work, we propose a novel expert-finding technique exploiting a hypergraph-based data model for MSNs. In particular, some user-ranking measures, obtained considering only particular useful hyperpaths, have been profitably used to evaluate the related expertness degree with respect to a given social topic. Several experiments on Last.FM have been performed to evaluate the proposed approach’s effectiveness, encouraging future work in this direction for supporting several applications such as multimedia recommendation, influence analysis, and so on.
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Gupta, B. B., and Somya Ranjan Sahoo. "Fake profile detection in multimedia big data on online social networks." International Journal of Information and Computer Security 12, no. 2/3 (2020): 303. http://dx.doi.org/10.1504/ijics.2020.10026785.

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Dissertations / Theses on the topic "Social and multimedia data"

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Wong, León Kevin, and Valdivia Diego Eduardo Antonio Rodríguez. "Distributed Social Media System - Multimedia Data Linkage." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2014. http://hdl.handle.net/10757/324525.

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Actualmente, las redes sociales en línea son uno de los principales medios donde se intercambia gran cantidad de información. En estas, los usuarios intentan reflejar su actividad diaria en forma de publicaciones en sus muros o de otros usuarios. Asimismo, las imágenes representan gran parte de la información sobre la actividad del usuario, por ejemplo, una foto en donde esté etiquetado. Estas interacciones del usuario en las redes ayudan a generar su identidad digital. La información revelada por la metadata de las imágenes enriquece este perfil y contribuye a mejorar los resultados en procesos como minería de datos, marketing, etc. El objetivo de este proyecto es generar un perfil digital en base a la información y actividad que contribuye un usuario a una red social, recopilando y mostrando explícitamente varios hechos que se revelan aprovechando la metadata de las imágenes y el factor temporal de la actividad en línea. Esto incluye el proceso de extracción, enriquecimiento y encapsulación de data en un modelo ontológico propuesto. Los resultados de los experimentos muestran que la información en el perfil, luego del enriquecimiento, es aproximadamente cuatro veces la información inicial, y la precisión de la nueva información está por encima del 75%. Trabajos futuros se inclinan hacia la detección del tipo de relación que existe entre una persona y uno de sus contactos. Asimismo, otro tema relevante a explorar incluye la extracción de un mayor rango de entidades, tales como eventos o temas de interés de un individuo, con el fin de mejorar el perfil digital del usuario. Finalmente, la minería de datos en el proceso de extracción de información ayudaría a enfocar mejor el marketing a los usuarios de redes sociales ya que dicha publicidad podría hacerse más personalizada. Palabras clave Linked data, información multimedia, perfil digital, redes sociales, metadata
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Bracamonte, Nole Teresa Jacqueline. "Improving web multimedia information retrieval using social data." Tesis, Universidad de Chile, 2018. http://repositorio.uchile.cl/handle/2250/168681.

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Tesis para optar al grado de Doctora en Ciencias, Mención Computación
Buscar contenido multimedia es una de las tareas más comunes que los usuarios realizan en la Web. Actualmente, los motores de búsqueda en la Web han mejorado la precisión de sus búsquedas de contenido multimedia y ahora brindan una mejor experiencia de usuarios. Sin embargo, estos motores aún no logran obtener resultados precisos para consultas que no son comunes, y consultas que se refieren a conceptos abstractos. En ambos escenarios, la razón principal es la falta de información preliminar. Esta tesis se enfoca en mejorar la recuperación de información multimedia en la Web usando datos generados a partir de la interacción entre usuarios y recursos multimedia. Para eso, se propone mejorar la recuperación de información multimedia desde dos perspectivas: (1) extrayendo conceptos relevantes a los recursos multimedia, y (2) mejorando las descripciones multimedia con datos generados por el usuario. En ambos casos, proponemos sistemas que funcionan independientemente del tipo de multimedia, y del idioma de los datos de entrada. En cuanto a la identificación de conceptos relacionados a objetos multimedia, desarrollamos un sistema que va desde los resultados de búsqueda específicos de la consulta hasta los conceptos detectados para dicha consulta. Nuestro enfoque demuestra que podemos aprovechar la vista parcial de una gran colección de documentos multimedia para detectar conceptos relevantes para una consulta determinada. Además, diseñamos una evaluación basada en usuarios que demuestra que nuestro algoritmo de detección de conceptos es más sólido que otros enfoques similares basados en detección de comunidades. Para mejorar la descripción multimedia, desarrollamos un sistema que combina contenido audio-visual de documentos multimedia con información de su contexto para mejorar y generar nuevas anotaciones para los documentos multimedia. Específicamente, extraemos datos de clicks de los registros de consultas y usamos las consultas como sustitutos para las anotaciones manuales. Tras una primera inspección, demostramos que las consultas proporcionan una descripción concisa de los documentos multimedia. El objetivo principal de esta tesis es demostrar la relevancia del contexto asociado a documentos multimedia para mejorar el proceso de recuperación de documentos multimedia en la Web. Además, mostramos que los grafos proporcionan una forma natural de modelar problemas multimedia.
Fondef D09I-1185, CONICYT-PCHA/Doctorado Nacional/2013-63130260, Apoyo a estadías corta de la Escuela de Postgrado de la U. de Chile, y el Núcleo Milenio CIWS
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Li, John Zhong. "Modeling and querying multimedia data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ29063.pdf.

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Amornraksa, Thumrongrat. "Data security for multimedia communications." Thesis, University of Surrey, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298091.

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Portnoy, Michael, and Hsueh-Szu Yang. "NETWORK DATA ACQUISITION AND PLAYBACK OF MULTIMEDIA DATA." International Foundation for Telemetering, 2006. http://hdl.handle.net/10150/604246.

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ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California
Traditional data acquisition systems have relied on physical connections between data sources and data receivers to handle the routing of acquired data streams. However, these systems grow exponentially in complexity as the number of data sources and receivers increases. New techniques are needed to address the ever increasing complexity of data acquisition. Furthermore, more advanced mechanisms are needed that move past the limitations of traditional data models that connect each data source to exactly one data receiver. This paper presents a software framework for the playback of multiplexed data acquired from a network acquisition system. This framework uses multicast technologies to connect data sources with multiple data receivers. The network acquisition system is briefly introduced before the software framework is discussed. Both the challenges and advantages involved with creating such a system are presented. Finally, this framework is applied to an aviation telemetry example.
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CARABALLO, ALEXANDER ARTURO MERA. "PUBLISHING ANNOTATED MULTIMEDIA DEEP WEB DATA." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23714@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Nos últimos anos, temos assistido um enorme crescimento de dados multimídia na Web. Novas tecnologias de menor custo e maior largura de banda têm permitido que a Web evolua para um formato multimídia. No entanto, a falta de ferramentas que podem tornar o formato multimídia disponível na Web nos levou a um conjunto de dados não-pesquisável e não indexável da Web, também conhecido como Deep Web. Desta forma, esta dissertação aborda o problema de como publicar conteúdo de áudio e vídeo na Web. Apresentamos uma ferramenta e uma nova abordagem que facilita a indexação e recuperação dos objetos com a ajuda das maquinas de busca tradicionais. A ferramenta gera automaticamente páginas Web estáticas que descrevem o conteúdo dos objetos e organizar esse conteúdo para facilitar a localização de segmentos do áudio ou vídeo que correspondem às descrições. As páginas Web estáticas podem ser traduzidos para outras línguas para atingir outras populações de usuários. Um processo de anotação também é realizado para incorporar dados legíveis pelas máquinas nas páginas Web. A dissertação também apresenta um experimento completo, publicando objetos de aprendizagem baseados em áudio e vídeo para avaliar a eficácia da abordagem.
In recent years, we witnessed a huge growth of multimedia data on the Web. New lower-cost technologies and greater bandwidth allowed the Web to evolve into a multimedia format. However, the lack of tools that can make multimedia format easily accessible on the Web led us to a non-searchable and non-indexable data of the Web, also known as Deep Web. In line with these observations, this dissertation addresses the problem of how to publish audio and video content on the Web. We present a tool and a novel approach that facilitates the indexing and retrieval of the objects with the help of traditional search engines. The tool automatically generates static Web pages that describe the content of the objects and organize this content to facilitate locating segments of the audio or video which correspond to the descriptions. The static Web pages can be translated to others languages to reach other user populations. An annotation process is also performed to embed machine-readable data into the Web pages. The dissertation also presents an in-depth experiment, publishing learning objects based on audio and video, to assess the efficacy of the technique.
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Klaghstan, Merza. "Multimedia data dissemination in opportunistic systems." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI125/document.

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Les réseaux opportunistes sont des réseaux mobiles qui se forment spontanément et de manière dynamique grâce à un ensemble d'utilisateurs itinérants dont le nombre et le déplacement ne sont pas prévisibles. En conséquence, la topologie et la densité de tels réseaux évoluent sans cesse. La diffusion de bout-en-bout d'informations, dans ce contexte, est incertaine du fait de la forte instabilité des liens réseaux point à point entre les utilisateurs. Les travaux qui en ont envisagé l'usage visent pour la plupart des applications impliquant l'envoi de message de petite taille. Cependant, la transmission de données volumineuses telles que les vidéos représente une alternative très pertinente aux réseaux d'infrastructure, en cas d'absence de réseau, de coût important ou pour éviter la censure d'un contenu. La diffusion des informations de grande taille en général et de vidéos en particulier dans des réseaux oppnets constitue un challenge important. En effet, permettre, dans un contexte réseau très incertain et instable, au destinataire d’une vidéo de prendre connaissance au plus vite du contenu de celle-ci, avec la meilleure qualité de lecture possible et en encombrant le moins possible le réseau reste un problème encore très largement ouvert. Dans cette thèse, nous proposons un nouveau mécanisme de diffusion de vidéos dans un réseau opportuniste de faible densité, visant à améliorer le temps d'acheminement de la vidéo tout en réduisant le délai de lecture à destination. La solution proposée se base sur le choix d'encoder la vidéo en utilisant l'encodage SVC, grâce auquel la vidéo se décline en un ensemble de couches interdépendantes (layers), chacune améliorant la précédente soit en terme de résolution, soit en terme de densité, soit en terme de perception visuelle. Notre solution se décline en trois contributions. La première consiste à proposer une adaptation du mécanisme de diffusion Spray-and-Wait, avec comme unités de diffusion, les couches produites par SVC. Les couches sont ainsi diffusées avec un niveau de redondance propre à chacune, adapté à leur degré d'importance dans la diffusion de la vidéo. Notre seconde contribution consiste à améliorer le mécanisme précédent en prenant en compte une granularité plus fine et adaptative en fonction de l'évolution de la topologie du réseau. Cette amélioration a la particularité de ne pas engendrer de coût de partitionnement, les couches vidéos dans l'encodage SVC étant naturellement déclinées en petites unités (NALU) à base desquelles l'unité de transfert sera calculée. Enfin, la troisième contribution de cette thèse consiste à proposer un mécanisme hybride de complétion des couches vidéos arrivées incomplètes à destination. Cette méthode se caractérise par le fait d'être initiée par le destinataire. Elle combine un protocole de demande des parties manquantes aux usagers proches dans le réseau et des techniques de complétion de vidéo à base d’opérations sur les frames constituant la vidéo
Opportunistic networks are human-centric mobile ad-hoc networks, in which neither the topology nor the participating nodes are known in advance. Routing is dynamically planned following the store-carry-and-forward paradigm, which takes advantage of people mobility. This widens the range of communication and supports indirect end-to-end data delivery. But due to individuals’ mobility, OppNets are characterized by frequent communication disruptions and uncertain data delivery. Hence, these networks are mostly used for exchanging small messages like disaster alarms or traffic notifications. Other scenarios that require the exchange of larger data are still challenging due to the characteristics of this kind of networks. However, there are still multimedia sharing scenarios where a user might need switching to an ad-hoc alternative. Examples are the cases of 1) absence of infrastructural networks in far rural areas, 2) high costs due limited data volumes or 3) undesirable censorship by third parties while exchanging sensitive content. Consequently, we target in this thesis a video dissemination scheme in OppNets. For the video delivery problem in the sparse opportunistic networks, we propose a solution that encloses three contributions. The first one is given by granulating the videos at the source node into smaller parts, and associating them with unequal redundancy degrees. This is technically based on using the Scalable Video Coding (SVC), which encodes a video into several layers of unequal importance for viewing the content at different quality levels. Layers are routed using the Spray-and-Wait routing protocol, with different redundancy factors for the different layers depending on their importance degree. In this context as well, a video viewing QoE metric is proposed, which takes the values of the perceived video quality, delivery delay and network overhead into consideration, and on a scalable basis. Second, we take advantage of the small units of the Network Abstraction Layer (NAL), which compose SVC layers. NAL units are packetized together under specific size constraints to optimize granularity. Packets sizes are tuned in an adaptive way, with regard to the dynamic network conditions. Each node is enabled to record a history of environmental information regarding the contacts and forwarding opportunities, and use this history to predict future opportunities and optimize the sizes accordingly. Lastly, the receiver node is pushed into action by reacting to missing data parts in a composite backward loss concealment mechanism. So, the receiver asks first for the missing data from other nodes in the network in the form of request-response. Then, since the transmission is concerned with video content, video frame loss error concealment techniques are also exploited at the receiver side. Consequently, we propose to combine the two techniques in the loss concealment mechanism, which is enabled then to react to missing data parts
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Lin, Lin. "Multimedia Data Mining and Retrieval for Multimedia Databases Using Associations and Correlations." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/434.

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With the explosion in the complexity and amount of pervasive multimedia data, there are high demands of multimedia services and applications in various areas for people to easily access and distribute multimedia data. Facing with abundance multimedia resources but inefficient and rather old-fashioned keyword-based information retrieval approaches, a content-based multimedia information retrieval (CBMIR) system is required to (i) reduce the dimension space for storage saving and computation reduction; (ii) advance multimedia learning methods to accurately identify target semantics for bridging the semantics between low-level/mid-level features and high-level semantics; and (iii) effectively search media content for dynamical media delivery and enable the extensive applications to be media-type driven. This research mainly focuses on multimedia data mining and retrieval system for multimedia databases by addressing some main challenges, such as data imbalance, data quality, semantic gap, user subjectivity and searching issues. Therefore, a novel CBMIR system is proposed in this dissertation. The proposed system utilizes both association rule mining (ARM) technique and multiple correspondence analysis (MCA) technique by taking into account both pattern discovery and statistical analysis. First, media content is represented by the global and local low-level and mid-level features and stored in the multimedia database. Second, a data filtering component is proposed in the system to improve the data quality and reduce the data imbalance. To be specific, the proposed filtering step is able to vertically select features and horizontally prune instances in multimedia databases. Third, a new learning and classification method mining weighted association rules is proposed in the retrieval system. The MCA-based correlation is used to generate and select the weighted N-feature-value pair rules, where the N varies from one to many. Forth, a ranking method independent of classifiers is proposed in the system to sort the retrieved results and put the most interesting ones on the top of the browsing list. Finally, a user interface is implemented in CBMIR system that allows the user to choose his/her interested concept, searches media based on the target concept, ranks the retrieved segments using the proposed ranking algorithm, and then displays the top-ranked segments to the user. The system is experimented with various high-level semantics from TRECVID benchmark data sets. TRECVID sound and vision data is a large data set, includes various types of videos, and has very rich semantics. Overall, the proposed system achieves promising results in comparison with the other well-known methods. Moreover, experiments that compare each component with some other famous algorithms are conducted. The experimental results show that all proposed components improve the functionalities of the CBMIR system, and the proposed system reaches effectiveness, robustness and efficiency for a high-dimensional multimedia database.
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Gibbons, Paul C. "Telecommunications services for multimedia data exchange support." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA271704.

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Fu, Haohuan. "Efficient multimedia data transmission over heterogeneous networks /." access full-text access abstract and table of contents, 2005. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-cs-b19887218a.pdf.

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Thesis (M. Phil.)--City University of Hong Kong, 2005.
"Submitted to Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Philosophy." Includes bibliographical references (leaves 105-108).
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Books on the topic "Social and multimedia data"

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Barrett, Edward. The Society of text: Hypertext, hypermedia, and the social construction of information. Cambridge, Mass: MIT Press, 1989.

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Florian, Alt, Michelis Daniel, and SpringerLink (Online service), eds. Pervasive Advertising. London: Springer-Verlag London Limited, 2011.

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Poland 2004) International Workshop on Intelligent Media Technology for Communicative Intelligence (2nd Warsaw. International Workshop on Intelligent Media Technology for Communicative Intelligence: Warsaw, Poland, September 13-14, 2004 : proceedings. Warsaw: PJIIT (Polish-Japanese Institute of Information Technology) Publishing House, 2004.

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service), SpringerLink (Online, ed. Handbook of Social Network Technologies and Applications. Boston, MA: Springer Science+Business Media, LLC, 2010.

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Facebook nation: Total information awareness. New York, N.Y: Springer, 2013.

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Perner, Petra, ed. Data Mining on Multimedia Data. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36282-7.

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Ramzan, Naeem. Social Media Retrieval. London: Springer London, 2013.

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Motorola. Multimedia device data. Phoenix, AZ: Motorola, 1995.

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Wu, Min. Multimedia Data Hiding. New York, NY: Springer New York, 2003.

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Wu, Min, and Bede Liu. Multimedia Data Hiding. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21754-3.

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Book chapters on the topic "Social and multimedia data"

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Roy, Suman Deb, and Wenjun Zeng. "Revelations from Social Multimedia Data." In Social Multimedia Signals, 135–42. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09117-4_10.

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Roy, Suman Deb, and Wenjun Zeng. "Data Visualization: Gazing at Ripples." In Social Multimedia Signals, 161–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09117-4_12.

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Niu, Teng, Shiai Zhu, Lei Pang, and Abdulmotaleb El Saddik. "Sentiment Analysis on Multi-View Social Data." In MultiMedia Modeling, 15–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27674-8_2.

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Kumar, Akshi, Saurabh Raj Sangwan, and Anand Nayyar. "Multimedia Social Big Data: Mining." In Intelligent Systems Reference Library, 289–321. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8759-3_11.

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Yuan, Jianbo, Quanzeng You, and Jiebo Luo. "Sentiment Analysis Using Social Multimedia." In Multimedia Data Mining and Analytics, 31–59. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14998-1_2.

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Cao, Liangliang, GuoJun Qi, Shen-Fu Tsai, Min-Hsuan Tsai, Andrey Del Pozo, Thomas S. Huang, Xuemei Zhang, and Suk Hwan Lim. "Multimedia Information Networks in Social Media." In Social Network Data Analytics, 413–45. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-8462-3_15.

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Bischke, Benjamin, Damian Borth, and Andreas Dengel. "Large-Scale Social Multimedia Analysis." In Big Data Analytics for Large-Scale Multimedia Search, 157–81. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119376996.ch6.

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Mirkovic, Milan, Dubravko Culibrk, and Vladimir Crnojevic. "Mining Geo-Referenced Community-Contributed Multimedia Data." In Computational Social Networks, 81–102. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4054-2_4.

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Wei, Ling-Yin, Yu Zheng, and Wen-Chih Peng. "Mining Popular Routes from Social Media." In Multimedia Data Mining and Analytics, 93–116. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14998-1_4.

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Amato, Flora, Giovanni Cozzolino, Francesco Moscato, Vincenzo Moscato, Antonio Picariello, and Giancarlo Sperli. "Data Mining in Social Network." In Intelligent Interactive Multimedia Systems and Services, 53–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92231-7_6.

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Conference papers on the topic "Social and multimedia data"

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Pang, Ran, Agustin Baretto, Henry Kautz, and Jiebo Luo. "Monitoring adolescent alcohol use via multimodal analysis in social multimedia." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363914.

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Ji, Rongrong, Donglin Cao, and Dazhen Lin. "Cross-Modality Sentiment Analysis for Social Multimedia." In 2015 IEEE International Conference on Multimedia Big Data (BigMM). IEEE, 2015. http://dx.doi.org/10.1109/bigmm.2015.85.

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Sang, Jitao, and Changsheng Xu. "On Analyzing the 'Variety' of Big Social Multimedia." In 2015 IEEE International Conference on Multimedia Big Data (BigMM). IEEE, 2015. http://dx.doi.org/10.1109/bigmm.2015.60.

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Jia, Jia. "Mental Health Computing via Harvesting Social Media Data." In MM '18: ACM Multimedia Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3267935.3267954.

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Xu, Dong, Lei Zhang, and Jiebo Luo. "Understanding multimedia content using web scale social media data." In the international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1873951.1874367.

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Broniatowski, David A. "Extracting social values and group identities from social media text data." In 2012 IEEE 14th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2012. http://dx.doi.org/10.1109/mmsp.2012.6343446.

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Zhou, Yiheng, Numair Sani, and Jiebo Luo. "Fine-grained mining of illicit drug use patterns using social multimedia data from instagram." In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7840812.

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Gao, Yue, Fanglin Wang, Huanbo Luan, and Tat-Seng Chua. "Brand Data Gathering From Live Social Media Streams." In ICMR '14: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2578726.2578748.

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Amato, Flora, Vincenzo Moscato, Antonio Picariello, and Giancarlo Sperli. "Recommendation in Social Media Networks." In 2017 IEEE Third International Conference on Multimedia Big Data (BigMM). IEEE, 2017. http://dx.doi.org/10.1109/bigmm.2017.55.

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Chang, Edward Y. "Organizing multimedia data socially." In the 2008 international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1386352.1386355.

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Reports on the topic "Social and multimedia data"

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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.

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The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.
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Rowe, Neil C., and Eugene J. Guglielmo. Exploiting Captions in Retrieval of Multimedia Data. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada255184.

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Kim, Kyung-Chang, and Vincent Y. Lum. Towards Intelligent Data Retrieval in Multimedia Databases. Fort Belvoir, VA: Defense Technical Information Center, February 1991. http://dx.doi.org/10.21236/ada243323.

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Davis, Timothy J. 10 Gbyte Personal Multimedia MEMS ROM Data Storage Card. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada388116.

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Iatsyshyn, Anna V., Iryna H. Hubeladze, Valeriia O. Kovach, Valentyna V. Kovalenko, Volodymyr O. Artemchuk, Maryna S. Dvornyk, Oleksandr O. Popov, Andrii V. Iatsyshyn, and Arnold E. Kiv. Applying digital technologies for work management of young scientists' councils. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4434.

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The publication explores the features of the digital technologies’ usage to organize the work of the Young Scientists’ Councils and describes the best practices. The digital transformation of society and the quarantine restrictions caused by the COVID-19 pandemic have forced the use of various digital technologies for scientific communication, the organization of work for youth associations, and the training of students and Ph.D. students. An important role in increasing the prestige of scientific activity and encouraging talented young people to participate in scientific projects belongs to the Young Scientists’ Councils, which are created at scientific institutions and higher education institutions. It is determined that the peculiarities of the work of Young Scientists’ Councils are in providing conditions for further staff development of the institution in which they operate; contribution to the social, psychological and material support of young scientists and Ph.D. students; creating an environment for teamwork and collaborative partnership; development of leadership and organizational qualities; contribution to the development of digital competence. The advantages of using electronic social networks in higher education and research institutions are analyzed, namely: general popularity and free of charge; prompt exchange of messages and multimedia data; user-friendly interface; availability of event planning functions, sending invitations, setting reminders; support of synchronous and asynchronous communication between network participants; possibility of access from various devices; a powerful tool for organizing the learning process; possibility of organization and work of closed and open groups; advertising of various events, etc. Peculiarities of managing the activity of the Young Scientists’ Council with the use of digital technologies are determined. The Young Scientists’ Council is a social system, and therefore the management of this system refers to social management. The effectiveness of the digital technologies’ usage to manage the activities of the Young Scientists’ Council depends on the intensity and need for their use to implement organizational, presentation functions and to ensure constant communication. The areas to apply digital technologies for the work managing of Young Scientists’ Councils are sorted as the presentation of activity; distribution of various information for young scientists; conducting questionnaires, surveys; organization and holding of scientific mass events; managing of thematic workgroups, holding of work meetings. It is generalized and described the experience of electronic social networks usage for organizing and conducting of scientific mass events.
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Ha, Kiryong, Padmanabhan Pillai, Grace Lewis, Soumya Simanta, Sarah Clinch, Nigel Davies, and Mahadev Satyanarayanan. The Impact of Mobile Multimedia Applications on Data Center Consolidation. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada570609.

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Strenge, D. L., and S. R. Peterson. Chemical data bases for the Multimedia Environmental Pollutant Assessment System (MEPAS). Office of Scientific and Technical Information (OSTI), December 1989. http://dx.doi.org/10.2172/6610163.

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Keim, Daniel A., Kyung-Chang Kim, and Vincent Y. Lum. A Friendly and Intelligent Approach to Data Retrieval in a Multimedia DBMS. Fort Belvoir, VA: Defense Technical Information Center, March 1991. http://dx.doi.org/10.21236/ada243284.

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Feng, Zhuo, Pritam Gundecha, Huan Liu, and Geoffrey Barbier. Provenance Data in Social Media. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ad1007370.

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Chetty, Raj, and Amy Finkelstein. Social Insurance: Connecting Theory to Data. Cambridge, MA: National Bureau of Economic Research, October 2012. http://dx.doi.org/10.3386/w18433.

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