Journal articles: '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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Sahoo, Somya Ranjan, and B. B. Gupta. "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.2020.105181.

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Ji, Xiangyang, Qifei Wang, Bo-Wei Chen, Seungmin Rho, C. C. Jay Kuo, and Qionghai Dai. "Online distribution and interaction of video data in social multimedia network." Multimedia Tools and Applications 75, no. 20 (November 25, 2014): 12941–54. http://dx.doi.org/10.1007/s11042-014-2335-1.

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Lee, Changhoon. "Guest Editorial: Automated Big Data Analysis for Social Multimedia Network Environments." Multimedia Tools and Applications 75, no. 20 (August 18, 2016): 12663–67. http://dx.doi.org/10.1007/s11042-016-3838-8.

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Dwirahayu, Gita Kartika. "INTERACTIVE POWERPOINT MULTIMEDIA INFLUENCE IN SOCIAL STUDIES LEARNING ON CONCEPT UNDERSTANDING OF STUDENT SOCIAL MOBILITY." International Journal Pedagogy of Social Studies 4, no. 1 (November 20, 2019): 51–56. http://dx.doi.org/10.17509/ijposs.v4i1.16096.

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One of the objectives of social studies is to recognize concepts related to people's lives and the environment. Social mobility is one of the material discussed in social studies learning and requires a more comprehensive understanding of students. One effort to improve the understanding of concepts in social studies learning is to use interactive multimedia PowerPoint. Through interactive multimedia PowerPoint, students are expected to be able to observe the concepts contained in learning material by absorbing as much information as possible through their senses so that they can improve the understanding of the concept of social mobility of students in social studies learning. The purpose of this study is to identify understanding of students' concepts when using interactive multimedia PowerPoint in social studies learning at Tasikmalaya 3rd Junior High School. The research method used a quasi experimental method with a nonequivalent control group design design pattern. The subjects of this study were Tasikmalaya 3rd Junior High School students there are class VIII B as the experimental class and class VIII C as the control class. The technique of collecting data is through tests of understanding the concepts of the pretest and posttest. Data analysis techniques using the normality test using chi square, homogeneity test using the F-test, and hypothesis testing using the t-test. The results showed an increase in the experimental class gain score on the three indicators, there are translation, interpretation, and extrapolation were higher than the control class. So that it can be concluded, social studies learning by using interactive PowerPoint multimedia is more effective in improving students' concepts understanding.

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Chen, Dr Joy Iong Zong, and Dr Smys S. "Social Multimedia Security and Suspicious Activity Detection in SDN using Hybrid Deep Learning Technique." June 2020 2, no. 2 (May 27, 2020): 108–15. http://dx.doi.org/10.36548/jitdw.2020.2.004.

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Social multimedia traffic is growing exponentially with the increased usage and continuous development of services and applications based on multimedia. Quality of Service (QoS), Quality of Information (QoI), scalability, reliability and such factors that are essential for social multimedia networks are realized by secure data transmission. For delivering actionable and timely insights in order to meet the growing demands of the user, multimedia analytics is performed by means of a trust-based paradigm. Efficient management and control of the network is facilitated by limiting certain capabilities such as energy-aware networking and runtime security in Software Defined Networks. In social multimedia context, suspicious flow detection is performed by a hybrid deep learning based anomaly detection scheme in order to enhance the SDN reliability. The entire process is divided into two modules namely – Abnormal activities detection using support vector machine based on Gradient descent and improved restricted Boltzmann machine which facilitates the anomaly detection module, and satisfying the strict requirements of QoS like low latency and high bandwidth in SDN using end-to-end data delivery module. In social multimedia, data delivery and anomaly detection services are essential in order to improve the efficiency and effectiveness of the system. For this purpose, we use benchmark datasets as well as real time evaluation to experimentally evaluate the proposed scheme. Detection of malicious events like confidential data collection, profile cloning and identity theft are performed to analyze the performance of the system using CMU-based insider threat dataset for large scale analysis.

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Ferraro, Antonino, Vincenzo Moscato, and Giancarlo Sperlì. "Deep Learning-Based Community Detection Approach on Multimedia Social Networks." Applied Sciences 11, no. 23 (December 2, 2021): 11447. http://dx.doi.org/10.3390/app112311447.

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Exploiting multimedia data to analyze social networks has recently become one the most challenging issues for Social Network Analysis (SNA), leading to defining Multimedia Social Networks (MSNs). In particular, these networks consider new ways of interaction and further relationships among users to support various SNA tasks: influence analysis, expert finding, community identification, item recommendation, and so on. In this paper, we present a hypergraph-based data model to represent all the different types of relationships among users within an MSN, often mediated by multimedia data. In particular, by considering only user-to-user paths that exploit particular hyperarcs and relevant to a given application, we were able to transform the initial hypergraph into a proper adjacency matrix, where each element represents the strength of the link between two users. This matrix was then computed in a novel way through a Convolutional Neural Network (CNN), suitably modified to handle high data sparsity, in order to generate communities among users. Several experiments on standard datasets showed the effectiveness of the proposed methodology compared to other approaches in the literature.

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Shyntore, G., L. Mukhamadiyeva, and A. Moldagulova. "DATA ANALYSIS OF SOCIAL NETWORKS BY SPLITTING INTO TEXT AND MULTIMEDIA COMPONENTS." Вестник Алматинского университета энергетики и связи, no. 1 (2020): 74–83. http://dx.doi.org/10.51775/1999-9801_2020_48_1_74.

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Nardi, Bonnie A., Allan Kuchinsky, Steve Whittaker, Robert Leichner, and Heinrich Schwarz. "Video-as-data: Technical and social aspects of a collaborative multimedia application." Computer Supported Cooperative Work (CSCW) 4, no. 1 (1994): 73–100. http://dx.doi.org/10.1007/bf00823364.

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Ennaji, Fatima Zohra, Abdelaziz El Fazziki, Hasna El Alaoui El Abdallaoui, Djamal Benslimane, and Mohamed Sadgal. "A product reputation framework based on social multimedia content." International Journal of Web Information Systems 16, no. 1 (September 11, 2019): 95–113. http://dx.doi.org/10.1108/ijwis-04-2019-0016.

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Purpose The purpose of this paper is to bring together the textual and multimedia opinions, since the use of social data has become the new trend that enables to gather the product reputation traded in social media. Integrating a product reputation process into the companies' strategy will bring several benefits such as helping in decision-making regarding the current and the new generation of the product by understanding the customers’ needs. However, image-centric sentiment analysis has received much less attention than text-based sentiment detection. Design/methodology/approach In this work, the authors propose a multimedia content-based product reputation framework that helps in detecting opinions from social media. Thus, in this case, the analysis of a certain publication is made by combining their textual and multimedia parts. Findings To test the effectiveness of the proposed framework, a case study based on YouTube videos has been established, as it brings together the image, the audio and the video processing at the same time. Originality/value The key novelty is the implication of multimedia content in addition of the textual one with the goal of gathering opinions about a certain product. The multimedia analysis brings together facial sentiment detection, printed text analysis, opinion detection from speeches and textual opinion analysis.

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Al-Khouri, Ali M. "Data Ownership: Who Owns 'My Data'?" INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 2, no. 1 (November 24, 2012): 1–8. http://dx.doi.org/10.24297/ijmit.v2i1.1406.

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The amount of data in our world today is substantially mammoth. Many of the personal and non-personal aspects of our day to day activities are aggregated and stored as data by both businesses and governments. The increasing data captured through multimedia, social media, and the Internet of Things is a phenomenon that needs to be properly examined. In this article, we explore this topic, and analyse the term data ownership. We aim to raise awareness and trigger debate for policy makers around data ownership and the need to improve existing data protection and privacy laws and legislation at both national and international levels.

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Yan, Yilin, Mei-Ling Shyu, and Qiusha Zhu. "Supporting Semantic Concept Retrieval with Negative Correlations in a Multimedia Big Data Mining System." International Journal of Semantic Computing 10, no. 02 (June 2016): 247–67. http://dx.doi.org/10.1142/s1793351x16400092.

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With the extensive use of smart devices and blooming popularity of social media websites such as Flickr, YouTube, Twitter, and Facebook, we have witnessed an explosion of multimedia data. The amount of data nowadays is formidable without effective big data technologies. It is well-acknowledged that multimedia high-level semantic concept mining and retrieval has become an important research topic; while the semantic gap (i.e., the gap between the low-level features and high-level concepts) makes it even more challenging. To address these challenges, it requires the joint research efforts from both big data mining and multimedia areas. In particular, the correlations among the classes can provide important context cues to help bridge the semantic gap. However, correlation discovery is computationally expensive due to the huge amount of data. In this paper, a novel multimedia big data mining system based on the MapReduce framework is proposed to discover negative correlations for semantic concept mining and retrieval. Furthermore, the proposed multimedia big data mining system consists of a big data processing platform with Mesos for efficient resource management and with Cassandra for handling data across multiple data centers. Experimental results on the TRECVID benchmark datasets demonstrate the feasibility and the effectiveness of the proposed multimedia big data mining system with negative correlation discovery for semantic concept mining and retrieval.

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Xu, Zheng, Zhiguo Yan, Yunhuai Liu, and Lin Mei. "Measuring the Semantic Relatedness Between Images Using Social Tags." International Journal of Cognitive Informatics and Natural Intelligence 7, no. 2 (April 2013): 1–12. http://dx.doi.org/10.4018/ijcini.2013040101.

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Relatedness measurement between multimedia such as images and videos plays an important role in computer vision, which is a base for many multimedia related applications including clustering, searching, recommendation, and annotation. Recently, with the explosion of social media, users can upload media data and annotate content with descriptive tags. In this paper, the authors aim at measuring the semantic relatedness of Flickr images. Firstly, information theory based functions are used to measure the semantic relatedness of tags. Secondly, the integration of tags pair based on bipartite graph is proposed to remove the noise and redundancy. The data sets including 1000 images from Flickr are used to evaluate the proposed method. Two data mining tasks including clustering and searching are performed by the proposed method, which shows the effectiveness and robust of the proposed method.

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Tyson, Gareth, Yehia Elkhatib, Nishanth Sastry, and Steve Uhlig. "Are People Really Social in Porn 2.0?" Proceedings of the International AAAI Conference on Web and Social Media 9, no. 1 (August 3, 2021): 436–44. http://dx.doi.org/10.1609/icwsm.v9i1.14601.

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Social Web 2.0 features have become a vital component in a variety of multimedia systems, e.g., YouTube, Last.fm. Interestingly, adult video websites are also starting to adopt these Web 2.0 principles, giving rise to the term "Porn 2.0". This paper examines a large Porn 2.0 social network, through data covering 563k users. We explore a number of unusual behavioural aspects that set this apart from more traditional multimedia social networks. We particularly focus on the role of gender and sexuality, to understand how these different groups behave. A number of key differences are discovered relating to social demographics, modalities of interaction and content consumption habits, shedding light on this understudied area of online activity.

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Ge, Mouzhi, and Fabio Persia. "A Generalized Evaluation Framework for Multimedia Recommender Systems." International Journal of Semantic Computing 12, no. 04 (December 2018): 541–57. http://dx.doi.org/10.1142/s1793351x18500046.

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With the widespread availability of media technologies, such as real-time streaming, new Internet-of-Thing devices and smart phones, multimedia data are extensively increased and the big multimedia data rapidly spread over various social networks. This has created complexity and information overload for users to choose the suitable multimedia objects. Thus, different multimedia recommender systems have been emerging to help users find the useful multimedia objects that are possibly preferred by the user. However, the evaluation of these multimedia recommender systems is still in an ad-hoc stage. Given the distinct features of multimedia objects, the evaluation criteria adopted from the general recommender systems might not be effectively used to evaluate multimedia recommendations. In this paper, we therefore review and analyze the evaluation criteria that have been used in the previous multimedia recommender system papers. Based on the review, we propose a generalized evaluation framework to guide the researchers and practitioners to perform evaluations, especially user-centric evaluations, for multimedia recommender systems.

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Fitra, Hawwin, Anggara Dwinata, Puji Hardati, and Leni Irmawati. "The Implementation of Interactive Multimedia on Critical Thinking Skills in Social Studies Learning for Elementary School Students." IJPSE : Indonesian Journal of Primary Science Education 3, no. 1 (November 14, 2022): 8–14. http://dx.doi.org/10.33752/ijpse.v3i1.3319.

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This study aims to implicitly analyze the use of interactive multimedia to improve critical thinking skills of elementary school students in Social Studies to face the era of society 5.0. This study uses a qualitative research method with a literature study research design. The steps taken by the researcher were initiated by formulating the research problem, then continued by tracing the relevant research results for analysis. Data was collected by searching electronic journals and studying documentation in the library. Based on the search results obtained research data from five electronic journals. Data analysis was carried out by summarizing, reviewing, and analyzing research data from several empirical research results. Based on the results of the analysis, it turns out that the use of interactive multimedia can improve learning outcomes with the results obtained by 23.33% and 38.1%, respectively. Interactive multimedia can also improve learning outcomes in Social Studies material with a yield of 7.8%. Interactive multimedia can also encourage students to think critically with 6% of the results. So that the critical thinking process will make it easier for students to realistically understand the Social Studies material for elementary school students with a result of 10.25%.

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A’yunn Angraeny, Anggun, and Adrian Alexander Suripatty. "Penggunaan Multimedia Sebagai Sarana Pemasaran Kiddiposh." Jurnal Indonesia Sosial Teknologi 2, no. 12 (December 21, 2021): 2118–30. http://dx.doi.org/10.36418/jist.v2i12.295.

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E-Commerce menjadi strategi pemasaran yang menjadi pilihan Kiddiposh dengan berbagai media yang digunakan, seperti penggunana website, social media, dan marketplace. Hal tersebut karena semakin banyaknya pengguna sarana digital yang juga dapat memberikan dampak positif pada penjualan produk Kiddiposh. Tujuan dalam penelitian ini adalah menganalisis penggunaan multimedia sebagai sarana pemasaran Kiddiposh. Metode penelitian ini menggunakan metode kualitatif dengan pendekatan studikasus dan Kiddiposh sebagai objek dalam penelitian. Penentuan lokasi penelitian dengan pertimbangan bahwa Kididposh merupakan salah satu bidang usaha yang menggunakan multimedia dalam kegiatan usahanya. Waktu penelitian dilakukan pada bulan Agustus dan September 2021. Data yang digunakan adalah data primer dan sekunder dengan menggunakan analisis interactive model yang diklasifikasikan dalam tiga langkah yaitu reduksi data, penyajian data, dan penarikan kesimpulan. Hasil dalam penelitian ini menunjukan bahwa Kiddiposh menggunakan media E-Commerce berupa website, social media Instagram, dan marketplace shopee dalam menawarkan produknya. Statistic kunjungan konsumen pada media E-Commerce Kiddiposh mengalami peningkatan setiap tahunnya. Hal tersebut diikuti dengan peningkatan penjualan produk Kiddiposh setiap tahunnya.

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Ye, Conghuan, Hefei Ling, Zenggang Xiong, Fuhao Zou, Cong Liu, and Fang Xu. "Secure Social Multimedia Big Data Sharing Using Scalable JFE in the TSHWT Domain." ACM Transactions on Multimedia Computing, Communications, and Applications 12, no. 4s (November 18, 2016): 1–23. http://dx.doi.org/10.1145/2978571.

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Zhou, Pan, Kehao Wang, Jie Xu, and Dapeng Wu. "Differentially-Private and Trustworthy Online Social Multimedia Big Data Retrieval in Edge Computing." IEEE Transactions on Multimedia 21, no. 3 (March 2019): 539–54. http://dx.doi.org/10.1109/tmm.2018.2885509.

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Wang, Fang. "The Effect of Multimedia Teaching Model of Music Course in Colleges and Universities Based on Classroom Audio Data Mining Technology." Tobacco Regulatory Science 7, no. 5 (September 30, 2021): 4520–31. http://dx.doi.org/10.18001/trs.7.5.2.18.

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Objectives: With the rapid development of information technology, multimedia teaching mode carries a large amount of audio-visual information, quickly occupies the music classroom in Colleges and universities, and becomes the mainstream teaching mode of music teaching in Colleges and universities. Methods: Based on this, this study uses classroom audio data mining technology to analyze the effect of multimedia teaching mode of music courses in Colleges and universities. The method of audio data mining is analyzed in college music multimedia classroom. The advanced embedded SOPC system is used to decode the MP3 audio files played in music courses by combining software and hardware. The performance of the multimedia teaching system in college music courses is optimized. Results: The hardware resources are made use of the flexibility of SOPC (System-on-a-Programmable-Chip) system. Reasonable allocation achieves the optimal design of teaching mode. Finally, the superiority of the algorithm is verified by testing. The test results show that the decoding speed and efficiency of audio files can be significantly improved by combining hardware and software. Conclusion: At the same time, the system has greater flexibility and expandable space, which can effectively promote the multimedia teaching effect of music courses in Colleges and universities. The research in this paper is helpful to the flexible transformation of multimedia teaching mode of music courses in Colleges and universities, and provides an important reference for the popularization of multimedia and the wide use of data mining technology in music courses in Colleges and universities.

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Amitani, Shigeki, Zafer Bilda, and Ernest Edmonds. "Our Content: generative montage methods for multimedia data." Design Studies 29, no. 6 (November 2008): 572–86. http://dx.doi.org/10.1016/j.destud.2008.07.007.

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Vlasova, Tatiana, Valentina Abraukhova, Natalia Mamchits, and Elena Egorova. "Content of multimedia orientations of students: risks and ways of their pedagogical overcoming in the framework of social partnership." SHS Web of Conferences 70 (2019): 03006. http://dx.doi.org/10.1051/shsconf/20197003006.

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The purpose of the study is to analyze the content of multimedia orientations of students who are real users of virtual space of the university. In the article next problems are exposed:1)new concept is ”content of multimedia orientations of students”;2)multimedia risks of students;3)the methods of overcoming of multimedia rrisks; 4) the model of social and pedagogical partnership; 5)the degree of multimedia orientations of students; 6) comparison of the obtained results with the research data related to the determination of students’ religious negativity, the phenomenon of which was reflected in their preferences in the selection of virtual information. The article discusses the relationship of the fourth industrial revolution and the digital economy; virtualistics and information and communication technologies; e-education and distance learning in the context of foreign and domestic scientific discourse, which allowed the introduction of new concepts in the field of professional pedagogy. Particular attention is paid to the methodological justification of cooperation between the aggregate subjects: students and teachers in the process of overcoming multimedia risks on the basis of the developed innovative model of social and pedagogical partnership in the system of higher professional education.

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Liao, Hong. "Analysis of the Multimedia Technology Influence in Basketball Game." Applied Mechanics and Materials 380-384 (August 2013): 2114–19. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.2114.

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with the development of modern technology, the multimedia technology has been widely applied in social production and life. In order to keep the game fair and impartial, the multimedia technology such as data statistics and management, game image analysis has been used in basketball game. This paper discusses the basic concept of multimedia technology and analyzes the application of multimedia technology in digital image communication in basketball competition. Based on this, it analyses the influence of multimedia technology's application in the basketball game, and makes a conclusion that the application of multimedia technology promotes the development of basketball game, but the negative influence caused by human factors can not be ignored during the operating process.

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Jang, Seok-Woo, and Gye-Young Kim. "Learning-Based Detection of Harmful Data in Mobile Devices." Mobile Information Systems 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3919134.

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The Internet has supported diverse types of multimedia content flowing freely on smart phones and tablet PCs based on its easy accessibility. However, multimedia content that can be emotionally harmful for children is also easily spread, causing many social problems. This paper proposes a method to assess the harmfulness of input images automatically based on an artificial neural network. The proposed method first detects human face areas based on the MCT features from the input images. Next, based on color characteristics, this study identifies human skin color areas along with the candidate areas of nipples, one of the human body parts representing harmfulness. Finally, the method removes nonnipple areas among the detected candidate areas using the artificial neural network. The experimental results show that the suggested neural network learning-based method can determine the harmfulness of various types of images more effectively by detecting nipple regions from input images robustly.

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Fu, Cai, Zhao Yang, Xiao-Yang Liu, Jia Yang, Anwar Walid, and Laurence T. Yang. "Secure Tensor Decomposition for Heterogeneous Multimedia Data in Cloud Computing." IEEE Transactions on Computational Social Systems 7, no. 1 (February 2020): 247–60. http://dx.doi.org/10.1109/tcss.2019.2959948.

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Long, Min, Fei Peng, and Xiaoqing Gong. "A Format-Compliant Encryption for Secure HEVC Video Sharing in Multimedia Social Network." International Journal of Digital Crime and Forensics 10, no. 2 (April 2018): 23–39. http://dx.doi.org/10.4018/ijdcf.2018040102.

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Aiming at secure video sharing in multimedia social network, a format-compliant encryption scheme for high efficiency video coding (HEVC) based on sigh data hiding (SDH) is proposed. The encryption is tightly integrated with the encoding/decoding processes. For each coding unit (CU), the sign of the nonzero coefficient and the first hiding nonzero coefficient are both encrypted with key stream. Meanwhile, one of merging index, motion vector prediction index, sign of motion vector difference and reference frame index is chosen for encryption according to a control factor. As it is explored in this article, experimental results and analysis indicate that it can effectively resist brute-force attack, difference attack and replacement attack. Also, it can keep a good balance in encryption space, computation complexity and security. Based on the encryption scheme, a framework of its implementation in multimedia social network is presented. It has great potential to be implemented for secure video sharing in multimedia social network.

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Hong, Seong-Yong, and Sung-Joon Lee. "An Intelligent Web Digital Image Metadata Service Platform for Social Curation Commerce Environment." Modelling and Simulation in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/651428.

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Information management includes multimedia data management, knowledge management, collaboration, and agents, all of which are supporting technologies for XML. XML technologies have an impact on multimedia databases as well as collaborative technologies and knowledge management. That is, e-commerce documents are encoded in XML and are gaining much popularity for business-to-business or business-to-consumer transactions. Recently, the internet sites, such as e-commerce sites and shopping mall sites, deal with a lot of image and multimedia information. This paper proposes an intelligent web digital image information retrieval platform, which adopts XML technology for social curation commerce environment. To support object-based content retrieval on product catalog images containing multiple objects, we describe multilevel metadata structures representing the local features, global features, and semantics of image data. To enable semantic-based and content-based retrieval on such image data, we design an XML-Schema for the proposed metadata. We also describe how to automatically transform the retrieval results into the forms suitable for the various user environments, such as web browser or mobile device, using XSLT. The proposed scheme can be utilized to enable efficient e-catalog metadata sharing between systems, and it will contribute to the improvement of the retrieval correctness and the user’s satisfaction on semantic-based web digital image information retrieval.

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Sperlì, Giancarlo, Flora Amato, Fabio Mercorio, Mario Mezzanzanica, Vincenzo Moscato, and Antonio Picariello. "A Social Media Recommender System." International Journal of Multimedia Data Engineering and Management 9, no. 1 (January 2018): 36–50. http://dx.doi.org/10.4018/ijmdem.2018010103.

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Social media recommendation differs from traditional recommendation approaches as it needs considering not only the content information and users' similarities, but also users' social relationships and behavior within an online social network as well. In this article, a recommender system – designed for big data applications – is used for providing useful recommendations in online social networks. The proposed technique represents a collaborative and user-centered approach that exploits the interactions among users and generated multimedia contents in one or more social networks in a novel and effective way. The experiments performed on data collected from several online social networks show the feasibility of the approach towards the social media recommendation problem.

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Khatir, Nadjia, and Safia Nait-bahloul. "Multi-criteria-based fusion for clustering texts and images case study on Flickr." Kybernetes 47, no. 10 (November 5, 2018): 1973–91. http://dx.doi.org/10.1108/k-01-2018-0030.

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Purpose This study aims to evaluate a new fusion technique of visual and textual clusters of objects from a real multimedia data-driven collection to improve the performance of multimedia applications. Design/methodology/approach The authors focused on using multi-criteria for clustering texts and images. The algorithm consists of these steps: first is text representation using the statistical method of weighting, second is image representation using a bag of words feature descriptors methods and finally application of multi-criteria clustering. Findings As an application for event detection based on social multimedia data, in particular, Flickr platform. Several experiments were conducted to choose the appropriate parameters for a better scheme of clustering. The new approach achieves better performance when aggregate text clustering is done with image clustering for event detection. Research limitations/implications Further researches would be investigated on other social media platforms such as Facebook and Twitter for a generalization of the technique. Originality/value This study contributes to multimedia data mining through the new fusion technique of clustering. The technique has its root in such strong field as the field of multi-criteria clustering and decision-making support.

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M E, Raghu, and K. C Ravishankar. "Encryption and Decryption of an Image Data – a Parallel Approach." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 674. http://dx.doi.org/10.14419/ijet.v7i3.34.19414.

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Multimedia data has been essential part of our lives, from instant messaging application to social media. Instant messaging applications like WhatsApp uses AES 256 bit key for security purpose. The security measures are taken so as to protect the data from unauthorized access and to ensure privacy. This paper mainly considers image data as source for encryption and decryption. Along with text, AES algorithm is used for image cryptography, in its suitable way. The AES algorithm is chosen because of its highly secured way of encryption and decryption. Time required for the procedure of encryption and decryption is also measured. Present use of Internet, mobile and socialmedia made images considerable value in our daily life. Securing multimedia data is becoming an important issue in communication and storage. Secured communication of digital images is needed in many areas, such as electronic commerce,medical imaging systems, mobile check deposit, online photograph album, military image communication, etc.., There is a need of developing fast encryption methodologies for such communication

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Rinaldi, Rinaldi, and Efrizon Efrizon. "Faktor-Faktor Yang Mempengaruhi Staf Pengajar Di Institusi Pendidikan Tinggi Untuk Menggunakan Multimedia." Elektron : Jurnal Ilmiah 6, no. 1 (June 15, 2014): 47–55. http://dx.doi.org/10.30630/eji.6.1.64.

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This study is a descriptive study of the application towards multimedia that conducted in higher institution, West Sumatera with the objectives of assessing the factors affecting multimedia application in higher institution lecturers. It employed a survey questionnaire to collect respondents’ responses by using Likert-5 point type scales. It was conducted on 250 lecturers by using stratified random sampling from three types of higher institutions. Data collected and analyzed by using Statistical for the Social Sciences 19.0 (SPSS 19.0). Descriptive analysis shows that factors affecting multimedia application are limited amount of equipments, less support from the institution, no confidence in using multimedia for teaching, damaged equipments, insufficient time to prepare multimedia-based teaching materials, not enough salaries to assist in carrying out their duties properly, increased teaching workloads, ineffective multimedia training and no rewards or incentives from the institution for using multimedia in teaching. As conclusion, this study can be used by the relevant authorities to take action in improving education.

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Gertrudis-Casado, María-Carmen, Manuel Gértrudix-Barrio, and Sergio Álvarez-García. "Professional information skills and open data. Challenges for citizen empowerment and social change." Comunicar 24, no. 47 (April 1, 2016): 39–47. http://dx.doi.org/10.3916/c47-2016-04.

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The current process of social transformation is driven by the growth of the culture of transparency and accountability, the socio-technological development of the web and the opening of public data. This situation forces the media to rethink their models of social intermediation, converting the growing open data access and user participation into new instruments that facilitate citizen empowerment. Open data can only generate citizen empowerment, facilitate decision-making and democratic action if it can provide valueadded information to the citizens. Therefore, the aim of the research is to analyse the competencies necessary to develop information products created with open data. The study used a qualitative methodology based on two instruments: a survey of data journalism experts (university professors of journalism, journalism professional data, and experts in transparency), and an analysis of selected cases of information products created with open data. The results allow the identification of a series of conceptual, procedural and attitudinal skills needed to perform the tasks of collection, processing, analysis and presentation of data, which are necessary for the development of this type of information product, and which should be integrated into the training of future journalists. Los actuales procesos de transformación social estimulados por el crecimiento de la cultura de transparencia y rendición de cuentas, el desarrollo socio-tecnológico de la web y la apertura de datos públicos, obliga a los medios de comunicación en el entorno digital a reorientar sus modelos de intermediación social, convirtiendo el creciente y complejo acceso a datos abiertos y los flujos de participación en nuevos instrumentos que faciliten el empoderamiento ciudadano. La investigación evalúa cuáles son las competencias profesionales necesarias para el desarrollo de productos informativos multimedia interactivos basados en datos abiertos, considerando que la apertura de datos solo generará empoderamiento ciudadano, facilitará la toma de decisiones y la acción democrática, si estos pueden proporcionar información de valor añadido para la ciudadanía. Para ello, se sigue una metodología cualitativa basada en dos instrumentos: una encuesta a expertos en periodismo de datos, relacionados con la formación superior en Periodismo, la legislación en materia de acceso a la información y los medios de comunicación, y el análisis de una muestra de productos informativos multimedia basados en datos abiertos. Los resultados permiten identificar una serie de competencias conceptuales, procedimentales y actitudinales necesarias para llevar a cabo las tareas de acopio, tratamiento, análisis y presentación de los datos, que son necesarias para el desarrollo de este tipo de productos informativos, y que deberían integrarse en la formación de los futuros comunicadores.

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Aisyah, Aznur, Intan Safinaz Zainudin, and Rou Seung Yoan. "Social Media Translational Action." International Journal of Virtual and Personal Learning Environments 9, no. 2 (July 2019): 32–54. http://dx.doi.org/10.4018/ijvple.2019070103.

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Internet application advancement has enabled Korean pop culture (K-Pop) to rapidly spread worldwide. However, technology alone is insufficient in delivering k-pop content to K-Pop fans because of language barriers. Hence, the translator's role is pivotal in decoding these data. Realising this crucial need, fans have acted as translators in interpreting enormous data file that have been improperly translated or unavailable in the original file. This research examined the translation process occurring in Twitter microblogging environment which is rarely analysed among linguistic scholars. the translation style of fan translators was identified, and the translational action involved discussed. K-Pop group, Bangtan Sonyeondan's (BTS) twitter account was selected as the main data source and Korean-English fan translation of the content distributed in the account was collected. The microblogging interface is equipped with the latest technology that supports multimedia data form, resulting in more dynamic translation work which needs to be highlighted in translation studies.

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Androutsos, P., D. Androutsos, and A. N. Venetsanopoulos. "Small world distributed access of multimedia data: an indexing system that mimics social acquaintance networks." IEEE Signal Processing Magazine 23, no. 2 (March 2006): 142–53. http://dx.doi.org/10.1109/msp.2006.1598090.

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Xu, Zheng, Xiangfeng Luo, Yunhuai Liu, Lin Mei, and Chuanping Hu. "Measuring Semantic Relatedness between Flickr Images: From a Social Tag Based View." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/758089.

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Relatedness measurement between multimedia such as images and videos plays an important role in computer vision, which is a base for many multimedia related applications including clustering, searching, recommendation, and annotation. Recently, with the explosion of social media, users can upload media data and annotate content with descriptive tags. In this paper, we aim at measuring the semantic relatedness of Flickr images. Firstly, four information theory based functions are used to measure the semantic relatedness of tags. Secondly, the integration of tags pair based on bipartite graph is proposed to remove the noise and redundancy. Thirdly, the order information of tags is added to measure the semantic relatedness, which emphasizes the tags with high positions. The data sets including 1000 images from Flickr are used to evaluate the proposed method. Two data mining tasks including clustering and searching are performed by the proposed method, which shows the effectiveness and robustness of the proposed method. Moreover, some applications such as searching and faceted exploration are introduced using the proposed method, which shows that the proposed method has broad prospects on web based tasks.

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Jung, Jongjin, Myungjin Kim, and Hanku Lee. "A Study on Efficient Design of A Multimedia Conversion Module in PESMS for Social Media Services." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 4 (August 1, 2015): 821. http://dx.doi.org/10.11591/ijece.v5i4.pp821-831.

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The main contribution of this paper is to present the Platform-as-a-Service<br />(PaaS) Environment for Social Multimedia Service (PESMS), derived from<br />the Social Media Cloud Computing Service Environment. The main role of<br />our PESMS is to support the development of social networking services that<br />include audio, image, and video formats. In this paper, we focus in particular on the design and implementation of PESMS, including the transcoding function for processing large amounts of social media in a parallel and distributed manner. PESMS is designed to improve the quality and speed of multimedia conversions by incorporating a multimedia conversion module based on Hadoop, consisting of Hadoop Distributed File System for storing large quantities of social data and MapReduce for distributed parallel processing of these data. In this way, our PESMS has the prospect of exponentially reducing the encoding time for transcoding large numbers of image files into specific formats. To test system performance for the transcoding function, we measured the image transcoding time under a variety of experimental conditions. Based on experiments performed on a 28-node cluster, we found that our system delivered excellent performance in the image transcoding function.

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Wen, Xiaoxian, Yunhui Ma, Jiaxin Fu, and Jing Li. "Application of clustering algorithm in social network user scenario prediction." Journal of Intelligent & Fuzzy Systems 39, no. 4 (October 21, 2020): 4971–79. http://dx.doi.org/10.3233/jifs-179982.

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In order to improve the ability of social network user behavior analysis and scenario pattern prediction, optimize social network construction, combine data mining and behavior analysis methods to perform social network user characteristic analysis and user scenario pattern optimization mining, and discover social network user behavior characteristics. Design multimedia content recommendation algorithms in multimedia social networks based on user behavior patterns. The current existing recommendation systems do not know how much the user likes the currently viewed content before the user scores the content or performs other operations, and the user’s preference may change at any time according to the user’s environment and the user’s identity, Usually in multimedia social networks, users have their own grading habits, or users’ ratings may be casual. Cluster-based algorithm, as an application of cluster analysis, based on clustering, the algorithm can predict the next position of the user. Because the algorithm has a “cold start”, it is suitable for new users without trajectories. You can also make predictions. In addition, the algorithm also considers the user’s feedback information, and constructs a scoring system, which can optimize the results of location prediction through iteration. The simulation results show that the accuracy of social network user scenario prediction using this method is higher, the accuracy of feature registration of social network user scenario mode is improved, and the real-time performance of algorithm processing is better.

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Kowshik, Kesavarapu, M. V S S Sandeep, Sai Gottipati Mounika, and Animesh Adhikari. "Analytic Method for Estimating the User Behavior Patterns in Multimedia Social Networks." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 427. http://dx.doi.org/10.14419/ijet.v7i2.32.15732.

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Now a days the multimedia social networks plays major role in our daily life. All the earlier MSNs are validated and developed very well. The past decade has witnessed the emergence and progress of multimedia social networks (MSNs), which have explosively and tremendously increased to penetrate every corner of our lives, leisure and work. As well as, the users are enabled by Mobile internet & terminals for accessing the MSNs where ever they are and when they want with the help of any identity. It may be a group or a role. So, it become very complicated & comprehensive to provide the behavior’s interaction between MSNs as well as in users. The implemented system having the advancements and developed framework of the analytics in a particular domain; which is called as SocialSitu, And We implemented an algorithm which is named as novel for the analysis of the serialized users intention according to the typical GSP which is the short form of Generalized Sequential Pattern. An enormous number of user’s behavior records were broken for exploring the usual sequence mode. It is mandatory for guessing the intention of the user. We considered the two types of intentions. Those are playing multimedia & sharing multimedia. These 2 are widely used in regular MSNs with the help of intention serialization algorithm in control of various min support threshold (Min_Support). With the help of microscopic behavior analysis of the users, we find out the each user behavior patterns which are in optimized manner in control of the Min_Support. Based on the different identities of the user, the behavior patterns of the users may be varied in session data which is very large.

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Yan, Yilin, and Mei-Ling Shyu. "Correlation-Assisted Imbalance Multimedia Concept Mining and Retrieval." International Journal of Semantic Computing 11, no. 02 (June 2017): 209–27. http://dx.doi.org/10.1142/s1793351x17400098.

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In the past decades, we have witnessed an explosion of multimedia data, especially with the development of social media websites and blooming popularity of smart devices. As a result, multimedia semantic concept mining and retrieval whose objective is to mine useful information from the large amount of multimedia data including texts, images, and videos has become more and more important. The huge amount of multimedia data and the semantic gap between low-level features and high-level semantic concepts have made it even more challenging. To address these challenges, the correlations among the classes can provide important context cues to help bridge the semantic gap. Meanwhile, many real-world datasets do not have uniform class distributions while the minority instances actually represent the concept of interests, like frauds in transactions, intrusions in network security, and unusual events in surveillance. Despite extensive research efforts, imbalanced concept retrieval remains one of the most challenging research problems in multimedia data mining. Different from existing frameworks regarding concept correlations among labels, this paper presents a novel concept correlation analysis model using the correlation between the retrieval scores and labels. Experimental results on the TRECVID benchmark datasets demonstrate that the proposed framework can enhance imbalanced concept mining and retrieval even with trivial scores from the minority class.

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Constantin, Mihai Gabriel, Karel Fliegel, and Maria Torres Vega. "Dataset Column: Overview, Scope and Call for Contributions." ACM SIGMultimedia Records 13, no. 3 (September 2021): 1. http://dx.doi.org/10.1145/3578495.3578499.

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The Dataset Column (https://records.sigmm.org/open-science/datasets/) of ACM SIGMM Records provides timely updates on the developments in the domain of publicly available multimedia datasets as enabling tools for reproducible research in numerous related areas. It is intended as a platform for further dissemination of useful information on multimedia datasets and studies of datasets covering various domains, published in peer-reviewed journals, conference proceedings, dissertations, or as results of applied research in industry. The aim of the Dataset Column is therefore not to substitute already established platforms for disseminating multimedia datasets, e.g., Qualinet Databases (https://qualinet.github.io/databases/) [2], Multimedia Evaluation Benchmark (https://multimediaeval.github.io/), but promote such platforms and particularly interesting datasets and benchmarking challenges associated with them. Multimedia Evaluation Benchmark, MediaEval 2021, registration is now open (https://multimediaeval.github.io). This year's MediaEval features a wide variety of tasks and datasets tackling a large number of domains, including video privacy, social media data analysis and understanding, news items analysis, medicine and wellbeing, affective and subjective content analysis, and game and sports associated media. The Column will also continue reporting of contributions presented within Dataset Tracks at relevant conferences, e.g., ACM Multimedia (MM), ACM Multimedia Systems (MMSys), International Conference on Quality of Multimedia Experience (QoMEX), International Conference on Multimedia Modeling (MMM).

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Mthethwa, Patrick. "A comparative Use of Traditional and Multimedia Modes of Teaching Curriculum Studies in English." TESOL and Technology Studies 3, no. 1 (May 30, 2022): 1–14. http://dx.doi.org/10.48185/tts.v3i1.389.

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This study explored students’ preferences on the use of traditional versus multimedia modes of course delivery at the University of Eswatini. Since the advent of technology, the use of traditional and multimedia modes of teaching has received a lot of attention in research. Students’ preferences regarding either being taught in a traditional or technological way is one of the areas that has been investigated intensively, yielding different conclusions. This study was a cross-sectional survey. For data collection, the study used a five-point anchored Likert-scale. Forty-three (43) participants participated in the study. They completed a questionnaire that sought their preferences on the mode of teaching between two courses, CTE 319/519 and CTE320/520. CTE319/519 was taught using multimedia, and CTE 320/520 was taught using the traditional mode. To establish the trends in the students’ preferences, data were analyzed using the statistical package for social science (SPSS), mainly descriptive statistics. The mean, frequencies, modes, and standard deviation were the major domains for data interpretation. The results revealed that the students preferred the use of multimedia over the traditional mode of course delivery. However, when the data were further analyzed using the age-range, the older generation performed better than the younger generation in their preferences on the use of multimedia when teaching. Overall, the results have implications for the integration of multimedia technology when teaching English courses at tertiary.

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Journal articles on the topic 'Social and multimedia data'

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