Special Issue "Intelligent Innovations in Multimedia Data"

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: closed (30 June 2020).

Special Issue Editors

Prof. Dr. Vincenzo Moscato
Website
Guest Editor
Department of Electrical Engineering and Information Technology, University of Naples "Federico II", Napoli, Italy.
Interests: multimedia, database systems, knowledge management, big data
Special Issues and Collections in MDPI journals
Dr. Giancarlo Sperlì

Guest Editor
Department of Electrical Engineering and Information Technology, University of Naples "Federico II", Napoli, Italy.
Dr. Stefano Marrone

Guest Editor
Department of Electrical Engineering and Information Technology, University of Naples "Federico II", Napoli, Italy.

Special Issue Information

Dear Colleagues,

In the last years, the spread of online social networks (OSNs) has provided users with new ways to interact on an interactive platform to create and share multimedia content such as text, image, video, audio, and so on. It is noteworthy that OSNs, both for the amount of data they produce and for the high peace of streaming, represent without any doubt the essence of big data.

As a consequence, this new availability of data has allowed researchers to investigate the suitability of big data, machine learning and, more recently, deep learning approaches to the development of intelligent innovations in multimedia data processing. Common applications include social dynamic analysis, user behavior prediction, multimedia content and social graph evolution modeling, computer vision, text mining and pattern discovery on graphs, usually aimed at designing human-centric multimedia applications and services, such as information retrieval, recommendation, summarization, viral marketing, event recognition, expert finding, community detection, user profiling, security and social data privacy.

The aim of this Special Issue is to collect the most recent innovation in the processing of multimedia data generated by user interaction and activities over online social networks. We would like to gather researchers from different disciplines and methodological backgrounds to discuss new ideas, research questions, recent results, and future challenges in this emerging area of research and public interest. Potential topics include, but are not limited to:

  • Multimedia information retrieval
  • Text processing and information mining
  • Multimedia recommendations
  • Spreading news on social media
  • Event detection
  • User profiling
  • Computer vision to track user habits and activities
  • Fake news detection and countermeasures

Prof. Dr. Vincenzo Moscato
Dr. Giancarlo Sperlì
Dr. Stefano Marrone
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Research

Open AccessArticle
Consortium Blockchain Smart Contracts for Musical Rights Governance in a Collective Management Organizations (CMOs) Use Case
Future Internet 2020, 12(8), 134; https://doi.org/10.3390/fi12080134 - 11 Aug 2020
Abstract
Private and permissioned blockchains are conceptualized and mostly assembled for fulfilling corporations’ demands and needs in the context of their own premises. This paper presents a complete and sophisticated end-to-end permissioned blockchain application for governance and management of musical rights endorsed by smart [...] Read more.
Private and permissioned blockchains are conceptualized and mostly assembled for fulfilling corporations’ demands and needs in the context of their own premises. This paper presents a complete and sophisticated end-to-end permissioned blockchain application for governance and management of musical rights endorsed by smart contract development. In a music industry use case, this disclosed solution monitors and regulates conflicting musical rights of diverse entities under a popular permissioned distributed ledger technology network. The proposed implementation couples various and distinct business domains across the music industry organizations and non-profit blockchain associations. Full article
(This article belongs to the Special Issue Intelligent Innovations in Multimedia Data)
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Open AccessArticle
Real-Time Stream Processing in Social Networks with RAM3S
Future Internet 2019, 11(12), 249; https://doi.org/10.3390/fi11120249 - 29 Nov 2019
Cited by 3
Abstract
The avalanche of (both user- and device-generated) multimedia data published in online social networks poses serious challenges to researchers seeking to analyze such data for many different tasks, like recommendation, event recognition, and so on. For some such tasks, the classical “batch” approach [...] Read more.
The avalanche of (both user- and device-generated) multimedia data published in online social networks poses serious challenges to researchers seeking to analyze such data for many different tasks, like recommendation, event recognition, and so on. For some such tasks, the classical “batch” approach of big data analysis is not suitable, due to constraints of real-time or near-real-time processing. This led to the rise of stream processing big data platforms, like Storm and Flink, that are able to process data with a very low latency. However, this complicates the task of data analysis since any implementation has to deal with the technicalities of such platforms, like distributed processing, synchronization, node faults, etc. In this paper, we show how the RAM 3 S framework could be profitably used to easily implement a variety of applications (such as clothing recommendations, job suggestions, and alert generation for dangerous events), being independent of the particular stream processing big data platforms used. Indeed, by using RAM 3 S, researchers can concentrate on the development of their data analysis application, completely ignoring the details of the underlying platform. Full article
(This article belongs to the Special Issue Intelligent Innovations in Multimedia Data)
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Open AccessArticle
A Context-Aware Conversational Agent in the Rehabilitation Domain
Future Internet 2019, 11(11), 231; https://doi.org/10.3390/fi11110231 - 01 Nov 2019
Cited by 2
Abstract
Conversational agents are reshaping our communication environment and have the potential to inform and persuade in new and effective ways. In this paper, we present the underlying technologies and the theoretical background behind a health-care platform dedicated to supporting medical stuff and individuals [...] Read more.
Conversational agents are reshaping our communication environment and have the potential to inform and persuade in new and effective ways. In this paper, we present the underlying technologies and the theoretical background behind a health-care platform dedicated to supporting medical stuff and individuals with movement disabilities and to providing advanced monitoring functionalities in hospital and home surroundings. The framework implements an intelligent combination of two research areas: (1) sensor- and camera-based monitoring to collect, analyse, and interpret people behaviour and (2) natural machine–human interaction through an apprehensive virtual assistant benefiting ailing patients. In addition, the framework serves as an important assistant to caregivers and clinical experts to obtain information about the patients in an intuitive manner. The proposed approach capitalises on latest breakthroughs in computer vision, sensor management, speech recognition, natural language processing, knowledge representation, dialogue management, semantic reasoning, and speech synthesis, combining medical expertise and patient history. Full article
(This article belongs to the Special Issue Intelligent Innovations in Multimedia Data)
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